IEEE Final Year PROJECTS & INTERNSHIP 9845166723 | 98866 92401: IEEE 2018 / 19

IEEE 2013: Property Analysis of XOR Based Visual Cryptography

IEEE 2013 Transactions on Image Processing

Abstracts : A (k, n) Visual Cryptographic Scheme (VCS) encodes a secret image into n shadow images (printed on Transparencies) distributed among n participants. When any k participants superimpose their transparencies on an overhead projector (OR operation), the secret image can be visually revealed by human visual system without computation. However, the monotone property of OR operation degrades the visual quality of reconstructed image for OR-based VCS (OVCS). Accordingly, XOR-based VCS (XVCS), which uses XOR operation for decoding, was proposed to enhance the contrast. In this paper, we investigate the relation between OVCS and XVCS. Our main contribution is to theoretically prove that the basis matrices of (k, n)-OVCS can be used in (k, n)-XVCS. Meantime, the contrast is enhanced 21) times-(k

IEEE 2013: Securing Visual Cryptographic Shares using Public Key Encryption

IEEE 2013 Transactions on Image Processing

Abstracts :The Visual Cryptography Scheme is a secure method that encrypts a secret document or image by breaking it into shares. A distinctive property of Visual Cryptography Scheme is that one can visually decode the secret image by superimposing shares without computation. By taking the advantage of this property, third person can easily retrieve the secret image if shares are passing in sequence over the network. The project presents an approach for encrypting visual cryptographically generated image shares using Public Key Encryption. RSA algorithm is used for providing the double security of secret document. Thus secret share are not available in their actual form for any alteration by the adversaries who try to create fake shares. The scheme provides more secure secret shares that are robust against a number of attacks & the system provides a strong security for the handwritten text, images and printed documents over the public network.

IEEE 2013: Super-Resolution-based In painting

IEEE 2013 Transactions on Image Processing

Abstracts :This paper introduces a new exemplar-based in painting frame-work. A coarse version of the input image is first in painted by a non-parametric patch sampling. Compared to existing approaches, some improvements have been done (e.g. filling order computation, combination of K nearest neighbor). The in painted of a coarse version of the input image allows to reduce the computational complexity, to be less sensitive to noise and to work with the dominant orientations of image structures. From the low-resolution in painted image, a single-image super-resolution is applied to recover the details of missing areas. Experimental results on natural images and texture synthesis demonstrate the effectiveness of the proposed method

IEEE 2013: Reversible Data Hiding in Encrypted Images by Reserving Room Before Encryption

IEEE 2013 Transactions on Information Forensics and Security

Abstracts :Recently, more and more attention is paid to reversible data hiding (RDH) in encrypted images, since it maintains the excellent property that the original cover can be losslessly recovered after embedded data is extracted while protecting the image content’s confidentiality. All previous methods embed data by reversibly vacating room from the encrypted images, which may be subject to some errors on data extraction and/or image restoration. In this paper, we propose a novel method by reserving room before encryption with a traditional RDH algorithm, and thus it is easy for the data hider to reversibly embed data in the encrypted image. The proposed method can achieve real reversibility, that is, data extraction and image recovery are free of any error. Experiments show that this novel method can embed more than 10 times as large payloads for the same image quality as the previous methods, such as for PSNR dB

IEEE 2013: EMR: A Scalable Graph-based Ranking Model for Content-based Image Retrieval

IEEE 2013 Transactions on Knowledge and Data Engineering

Graph-based ranking models have been widely applied in information retrieval area. In this paper, we focus on a well known graph-based model - the Ranking on Data Mani fold model, or Manifold Ranking (MR). Particularly, it has been successfully applied to content-based image retrieval, because of its outstanding ability to discover underlying geometrical structure of the given image database. However, manifold ranking is computationally very expensive, which significantly limits its applicability to large databases especially for the cases that the queries are out of the database (new samples). We propose a novel scalable graph-based ranking model called Efficient Manifold Ranking (EMR), trying to address the shortcomings of MR from two main perspectives: scalable graph construction and efficient ranking computation. Specifically, we build an anchor graph on the database instead of a traditional k-nearest neighbor graph, and design a new form of adjacency matrix utilized to speed up the ranking. An approximate method is adopted for efficient out-of-sample retrieval. Experimental results on some large scale image databases demonstrate that EMR is a promising method for real world retrieval applications.

IEEE 2013: Steganography using Genetic Algorithm along with Visual Cryptography for Wireless Network Application

Image Stenography is an emerging field of research for secure data hiding and transmission over networks. The proposed system provides the best approach for Least Significant Bit (LSB) based Stenography using Genetic Algorithm (GA) along with Visual Cryptography (VC). Original message is converted into cipher text by using secret key and then hidden into the LSB of original image. Genetic Algorithm and Visual Cryptography has been used for enhancing the security. Genetic Algorithm is used to modify the pixel location of stego image and the detection of this message is complex. Visual Cryptography is used to encrypt the visual information. It is achieved by breaking the image into two shares based on a threshold. The performance of the proposed system is experimented by performing steganalysis and conducting benchmarking test for analysing the parameters like Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The main aim of this paper is to design the enhanced secure algorithm which uses both steganography using Genetic Algorithm and Visual Cryptography to ensure improved security and reliability.

IEEE 2013: Scalable Face Image Retrieval using Attribute-Enhanced Sparse Code words
IEEE 2013 Transactions on Multimedia

Photos with people (e.g., family, friends, celebrities, etc.) are the major interest of users. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In this work, we aim to utilize automatically detected human attributes that contain semantic cues of the face photos to improve content-based face retrieval by constructing semantic code words for efficient large-scale face retrieval. By leveraging human attributes in a scalable and systematic framework, we propose two orthogonal methods named attribute-enhanced sparse coding and attribute-embedded inverted indexing to improve the face retrieval in the offline and online stages. We investigate the effectiveness of different attributes and vital factors essential for face retrieval. Experimenting on two public data sets, the results show that the proposed methods can achieve up to 43.5% relative improvement in MAP compared to the existing method

IEEE 2013: AN EXTENDED VISUAL CRYPTOGRAPHY SCHEME WITHOUT PIXEL EXPANSION FOR HALFTONE IMAGES

Visual cryptography is a secret sharing scheme which uses images distributed as shares such that, when the shares are superimposed, a hidden secret image is revealed. In extended visual cryptography, the share images are constructed to contain meaningful cover images, thereby providing opportunities for integrating visual cryptography and biometric security techniques. In this paper, we propose a method for processing halftone images that improves the quality of the share images and the recovered secret image in an extended visual cryptography scheme for which the size of the share images and there covered image is the same as for the original halftone secret image. The resulting scheme maintains the perfect security of the original extended visual cryptography approach

IEEE 2013: An Encryption and Decryption Algorithm for Image Based on DNA

IEEE 2013 Transactions on Communication Systems and Network Technologies

A novel image encryption algorithm based on DNA sequence addition operation. This initiation and increasing escalation of Internet has caused the information to be paperless and the makeover into electronic compared to the conventional digital image distribution. In this paper we proposed and implement four phase. First phase, image is renovating into binary matrix. Afterward matrix is apportioning into equal blocks. Second phase, each block is then encoded into DNA sequences and DNA sequence addition operation used to add these blocks. For that result of added matrix is achieved by using two Logistic maps. At the time of decoding the DNA sequence matrix is complemented and we encrypt that result by using DES then we get encrypted image. Our paper includes a novel encryption technique for providing security to image. We have proposed an algorithm which is based on suitable encryption method

IEEE 2013: Combined texture and Shape Features for Content Based Image Retrieval

IEEE 2013 Transactions on Power and Computing Technologies

Image retrieval refers to extracting desired images from a large database. The retrieval may be of text based or content based. Here content based image retrieval (CBIR) is performed. CBIR is a long standing research topic in the field of multimedia. Here features such as texture & shape are analyzed. Gabor filter is used to extract texture features from images. Morphological c10sing operation combined with Gabor filter gives better retrieval accuracy. The parameters considered are scale and orientation. After applying Gabor filter on the image, texture features such as mean and standard deviations are calculated. This forms the feature vector. Shape feature is extracted by using Fourier Descriptor and the centroid distance. In order to improve the retrieval performance, combined texture and shape features are utilized, because many features provide more information than the single feature. The images are extracted based on their Euclidean distance. The performance is evaluated using precision-recall graph.

IEEE 2013: Beyond Text QA: Multimedia Answer Generation by Harvesting Web Information

IEEE 2013 Transactions on multimedia

Community question answering (cQA) services have gained popularity over the past years. It not only allows community members to post and answer questions but also enables general users to seek information from a comprehensive set of well-answered questions. However, existing cQA forums usually provide only textual answers, which are not informative enough for many questions. In this paper, we propose a scheme that is able to en-rich textual answers in cQA with appropriate media data. Our scheme consists of three components: answer medium selection, query generation for multimedia search, and multimedia data selection and presentation. This approach automatically determines which type of media information should be added for a textual answer. It then automatically collects data from the web to enrich the answer. By processing a large set of QA pairs and adding them to a pool, our approach can enable a novel multimedia question answering (MMQA) approach as users can find multimedia answers by matching their questions with those in the pool. Different from a lot of MMQA research efforts that attempt to directly answer questions with image and video data, our approach is built based on community-contributed textual answers and thus it is able to deal
with more complex questions. We have conducted extensive experiments on a multi source QA data set. The results demonstrate the effectiveness of our approach

IEEE 2013:A Web Usage Mining Approach Based On New Technique In Web Path Recommendation Systems

IEEE 2013 Transactions on Engineering Research & Technology

A Web Usage Mining Approach Based On New Technique In Web Path Recommendation Systems The Internet is one of the fastest growing areas of intelligence gathering. The ranking of web page for the Web search-engine is one of the significant problems at present. This leads to the important attention to the research community. Web Perfecting is used to reduce the access latency of the Internet. However, if most perfected Web pages are not visited by the users in their subsequent accesses, the limited network bandwidth and server resources will not be used efficiently and may worsen the access delay problem. Therefore, it is critical that we have an accurate prediction method during perfecting. To provide prediction efficiently, we advance architecture for predicting in Web Usage Mining system and propose a novel approach for classifying user navigation patterns for predicting users’ requests based on clustering users browsing behavior knowledge. The Excremental results show that the approach can improve accuracy, precision, recall and F measure of classification in the architecture

IEEE 2013: SUSIE: Search Using Services and Information Extraction

IEEE 2013 Transactions on Knowledge and Data Engineering

restricts the types of queries that the service can answer. For example, a Web service might provide a method that returns the songs of a given singer, but it might not provide a method that returns the singers of a given song. If the user asks for the singer of some specific song, then the Web service cannot be called – even though the underlying database might have the desired piece of information. This asymmetry is particularly problematic if the service is used in a Web service orchestration system. In this paper, we propose to use on-the-fly information extraction to collect values that can be used as parameter bindings for the Web service. We show how this idea can be integrated into a Web service orchestration system. Our approach is fully implemented in a prototype called SUSIE. We present experiments with real-life data and services to demonstrate the practical viability and good performance of our approach.

IEEE 2013:PMSE: A Personalized Mobile Search Engine
IEEE 2013 Transactions on Knowledge and Data Engineering

We propose a personalized mobile search engine (PMSE) that captures the users’ preferences in the form of concepts by mining their click through data. Due to the importance of location information in mobile search, PMSE classifies these concepts into content concepts and location concepts. In addition, users’ locations (positioned by GPS) are used to supplement the location concepts in PMSE. The user preferences are organized in an ontology-based, multifacet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results. To characterize the diversity of the concepts associated with a query and their relevance to the user’s need, four entropies are introduced to balance the weights between the content and location facets. Based on the client-server model, we also present a detailed architecture and design for implementation of PMSE. In our design, the client collects and stores locally the click through data to protect privacy, whereas heavy tasks such as concept extraction, training, and re ranking are performed at the PMSE server. Moreover, we address the privacy issue by restricting the information in the user profile exposed to the PMSE server with two privacy parameters. We prototype PMSE on the Google Android platform. Experimental results show that PMSE significantly improves the precision comparing to the baseline.

IEEE 2013: Generation of Personalized Ontology Based on Consumer Emotion and Behavior Analysis

IEEE 2013 Transactions on Affective Computing

The relationships between consumer emotions and their buying behaviors have been well documented. Technology-savvy consumers often use the web to find information on products and services before they commit to buying. We propose a semantic web usage mining approach for discovering periodic web access patterns from annotated web usage logs which incorporates information on consumer emotions and behaviors through self-reporting and behavioral tracking. We use fuzzy logic to represent real-life temporal concepts (e.g., morning) and requested resource attributes (ontological domain concepts for the requested URLs) of periodic pattern-based web access activities. These fuzzy temporal and resource representations, which contain both behavioral and emotional cues, are incorporated into a Personal Web Usage Lattice that models the user’s web access activities. From this, we generate a Personal Web Usage Ontology written in OWL, which enables semantic web applications such as personalized web resources recommendation. Finally, we demonstrate the effectiveness of our approach by presenting experimental results in the context of personalized web resources recommendation with varying degrees of emotional influence. Emotional influence has been found to contribute positively to adaptation in personalized recommendation

IEEE 2013: Identity-Based Secure Distributed Data Storage Schemes

IEEE 2013 Transactions on Computers

Secure distributed data storage can shift the burden of maintaining a large number of files from the owner to proxy servers. Proxy servers can convert encrypted files for the owner to encrypted files for the receiver without the necessity of knowing the content of the original files. In practice, the original files will be removed by the owner for the sake of space efficiency. Hence, the issues on confidentiality and integrity of the outsourced data must be addressed carefully. In this paper, we propose two identity-based secure distributed data storage (IBSDDS) schemes. Our schemes can capture the following properties: The file owner can decide the access permission independently without the help of the private key generator (PKG); For one query, a receiver can only access one file, instead of all files of the owner; Our schemes are secure against the collusion attacks, namely even if the receiver can compromise the proxy servers, he cannot obtain the owner’s secret key. Although the first scheme is only secure against the chosen plain text attacks (CPA), the second scheme is secure against the chosen cipher text attacks (CCA). To the best of our knowledge, it is the first IBSDDS schemes where an access permissions is made by the owner for an exact file and collusion attacks can be protected

in the standard model.

IEEE 2013: Ginix: Generalized Inverted Index for Keyword Search

IEEE 2013 Transactions on Knowledge and Data Mining

Keyword search has become a ubiquitous method for users to access text data in the face of information explosion. Inverted lists are usually used to index underlying documents to retrieve documents according to a set of keywords efficiently. Since inverted lists are usually large, many compression techniques have been proposed to reduce the storage space and disk I/O time. However, these techniques usually perform decompression operations on the fly, which increases the CPU time. This paper presents a more efficient index structure, the Generalized INverted IndeX (Ginix), which merges consecutive IDs in inverted lists into intervals to save storage space. With this index structure, more efficient algorithms can be devised to perform basic keyword search operations, i.e., the union and the intersection operations, by taking the advantage of intervals. Specifically, these algorithms do not require conversions from interval lists back to ID lists. As a result, keyword search using Ginix can be more efficient than those using traditional inverted indices. The performance of Ginix is also improved by reordering the documents in data sets using two scalable algorithms. Experiments on the performance and scalability of Ginix on real data sets show that Ginix not only requires less storage space, but also improves the keyword search performance, compared with traditional inverted indexes

IEEE 2013: An Ontology-based Framework for Context-aware Adaptive E-learning System

IEEE 2013 Transactions on Computer Communication and Informatics

in web-based e-learning environment every learner has a distinct background, learning style and a specific goal when searching for learning material on the web. The goal of personalization is to tailor search results to a particular user based on that user’s contextual information. The effectiveness of accessing learning material involves two important challenges: identifying the user context and modeling the user context as ontological profiles. This work describes the ontology-based framework for context-aware adaptive learning system, with detailed discussions on the categorization contextual information and modeling along with the use of ontology to explicitly specify learner context in an e-learning environment. Finally we conclude by showing the applicability of the proposed ontology with appropriate architectural overview of e-learning system

IEEE 2013: ELCA Evaluation for Keyword Search on Probabilistic XML Data

IEEE 2013 Transactions on Knowledge and Data Engineering

As probabilistic data management is becoming one of the main re-search focuses and keyword search is turning into a more popular query means, it is natural to think how to support keyword queries on probabilistic XML data. With regards to keyword query on De-terministic XML documents, ELCA (Exclusive Lowest Common Ancestor) semantics allows more relevant fragments rooted at the ELCAs to appear as results and is more popular compared with other keyword query result semantics (such as SLCAs). In this paper, we investigate how to evaluate ELCA results for keyword queries on probabilistic XML documents. After defin-ing probabilistic ELCA semantics in terms of possible world se-mantics, we propose an approach to compute ELCA probabilities without generating possible worlds. Then we develop an efficient stack-based algorithm that can find all probabilistic ELCA results and their ELCA probabilities for a given keyword query on a prob-abilistic XML document. Finally, we experimentally evaluate the proposed ELCA algorithm and compare it with its SLCA counter-part in aspects of result effectiveness, time and space efficiency, and scalability

IEEE 2013: Crowd sourcing Predictors of Behavioral Outcomes

IEEE 2013:Transactions on Knowledge and Data Engineering

Generating models from large data sets—and deter-mining which subsets of data to mine—is becoming increasingly automated. However choosing what data to collect in the first place requires human intuition or experience, usually supplied by a domain expert. This paper describes a new approach to machine science which demonstrates for the first time that non-domain experts can collectively formulate features, and provide values for those features such that they are predictive of some behavioral outcome of interest. This was accomplished by building a web platform in which human groups interact to both respond to questions likely to help predict a behavioral outcome and pose new questions to their peers. This results in a dynamically-growing online survey, but the result of this cooperative behavior also leads to models that can predict user’s outcomes based on their responses to the user-generated survey questions. Here we describe two web-based experiments that instantiate this approach: the first site led to models that can predict users’ monthly electric energy consumption; the other led to models that can predict users’ body mass index. As exponential increases in content are often observed in successful online collaborative communities, the proposed methodology may, in the future, lead to similar exponential rises in discovery and insight into the causal factors of behavioral outcomes

IEEE 2013: Facilitating Document Annotation using Content and Querying Value

IEEE 2013 Transactions on Knowledge and Data Engineering in cloud

A large number of organizations today generate and share textual descriptions of their products, services, and actions. Such collections of textual data contain significant amount of struc-tured information, which remains buried in the unstructured text. While information extraction algorithms facilitate the extraction of structured relations, they are often expensive and inaccurate, es-pecially when operating on top of text that does not contain any instances of the targeted structured information. We present a novel alternative approach that facilitates the generation of the structured metadata by identifying documents that are likely to contain informa-tion of interest and this information is going to be subsequently useful for querying the database. Our approach relies on the idea that hu-mans are more likely to add the necessary metadata during creation time, if prompted by the interface; or that it is much easier for humans (and/or algorithms) to identify the metadata when such information actually exists in the document, instead of naively prompting users to fill in forms with information that is not available in the document. As a major contribution of this paper, we present algorithms that identify structured attributes that are likely to appear within the document, by jointly utilizing the content of the text and the query workload. Our experimental evaluation shows that our approach generates superior results compared to approaches that rely only on the textual content or only on the query workload, to identify attributes of interest

IEEE 2013: Geo-Community-Based Broadcasting for Data Dissemination in Mobile Social Networks

IEEE 2013 Transactions on Parallel and Distributed System

Abstract—In this paper, we consider the issue of data broadcasting in mobile social Networks (MSNets). The objective is to broadcast data from a super user to other users in the network. There are two main challenges under this paradigm, namely, how to represent and characterize user mobility in realistic MSN ets; given the knowledge of regular users’ movements, how to design an efficient super user route to broadcast data actively. We first explore several realistic data sets to reveal both geographic and social regularities of human mobility, and further propose the concepts of Geo-community and Geo-centrality into MSNet analysis. Then, we employ a semi-Markov process to model user mobility based on the Geo-community structure of the network. Correspondingly, the Geo-centrality indicating the “dynamic user density” of each Geo-community can be derived from the semi-Markov model. Finally, considering the Geo-centrality information, we provide different route algorithms to cater to the superuser that wants to either minimize total duration or maximize dissemination ratio. To the best of our knowledge, this work is the first to study data broadcasting in a realistic MSNet setting. Extensive trace-driven simulations show that our approach consistently outperforms other existing super user route design algorithms in terms of dissemination ratio and energy efficiency

IEEE 2013: Distributed Cooperative Caching in Social Wireless Networks

IEEE 2013 Transactions on Mobile Computing

Abstract—This paper introduces cooperative caching policies for minimizing electronic content provisioning cost in Social Wireless Networks (SWNET). SWNETs are formed by mobile devices, such as data enabled phones, electronic book readers etc., sharing common interests in electronic content, and physically gathering together in public places. Electronic object caching in such SWNETs are shown to be able to reduce the content provisioning cost which depends heavily on the service and pricing dependence among various stakeholders including content providers (CP), network service providers, and End Consumers (EC). Drawing motivation from Amazon’s Kindle electronic book delivery business, this paper develops practical network, service, and pricing models which are then used for creating two object caching strategies for minimizing content provisioning costs in networks with homogenous and heterogeneous object demands. The paper constructs analytical and simulation models for analyzing the proposed caching strategies in the presence of selfish users that deviate from network-wide cost-optimal policies. It also reports results from an Android phone-based prototype SWNET, validating the presented analytical and simulation results.

IEEE 2013: CPU Scheduling for Power/Energy Management on Multi core Processors Using Cache Miss and Context Switch Data

IEEE 2013 Transactions on Parallel and Distributed System

Abstract— Power and energy have become increasingly important concerns in the design and implementation of today’s multi core/many core chips. In this paper we present two priority-based CPU scheduling algorithms, Algorithm Cache Miss Priority CPU Scheduler (CM−PCS) and Algorithm Context Switch Priority CPU Scheduler(CS−PCS), which take advantage of often ignored dynamic performance data, in order to reduce power consumption by over 20% with a significant increase in performance. Our algorithms utilize Linux cpu sets and cores operating at different fixed frequencies. Many other techniques, including dynamic frequency scaling, can lower a core’s frequency during the execution of a non-CPU intensive task, thus lowering performance. Our algorithms match processes to cores better suited to execute those processes in an effort to lower the average completion time of all processes in an entire task, thus improving performance. They also consider a process’s cache miss/cache reference ratio, number of context switches and CPU migrations, and system load. Finally, our algorithms use dynamic process priorities as scheduling criteria. We have tested our algorithms using a real AMD Opteron 6134 multi core chip and measured results directly using the “Kill A Watt” meter, which samples power periodically during execution. Our results show not only a power (energy/execution time) savings of 39 watts (21.43%) and 38 watts (20.88%), but also a significant improvement in the performance, performance per watt, and execution time ·watt (energy) for a task consisting of twenty-four concurrently executing benchmarks, when compared to the default Linux scheduler and CPU frequency scaling governor.

IEEE 2013: DCIM: Distributed Cache Invalidation Method for Maintaining Cache Consistency in Wireless Mobile Networks

IEEE 2013 Transactions on Mobile Computing

Abstract—This paper proposes distributed cache invalidation mechanism (DCIM), a client-based cache consistency scheme that is implemented on top of a previously proposed architecture for caching data items in mobile ad hoc networks (MANETs), namely COACS, where special nodes cache the queries and the addresses of the nodes that store the responses to these queries. We have also previously proposed a server-based consistency scheme, named SSUM, whereas in this paper, we introduce DCIM that is totally client-based. DCIM is a pull-based algorithm that implements adaptive time to live (TTL), piggybacking, and perfecting, and provides near strong consistency capabilities. Cached data items are assigned adaptive TTL values that correspond to their update rates at the data source, where items with expired TTL values are grouped in validation requests to the data source to refresh them, whereas unexpired ones but with high request rates are prefetched from the server. In this paper, DCIM is analyzed to assess the delay and bandwidth gains (or costs) when compared to polling every time and push-based schemes. DCIM was also implemented using ns2, and compared against client-based and server-based schemes to assess its performance experimentally. The consistency ratio, delay, and overhead traffic are reported versus several variables, where DCIM showed to be superior when compared to the other systems.

IEEE 2013: Detection and Localization of Multiple Spoofing Attackers in Wireless Networks

IEEE 2013 Transactions on Parallel and Distributed System

Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. In this paper, we propose to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for detecting spoofing attacks; determining the number of attackers when multiple adversaries masquerading as the same node identity; and localizing multiple adversaries. We propose to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. We then formulate the problem of determining the number of attackers as a multi class detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, we explore using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. In addition, we developed an integrated detection and localization system that can localize the positions of multiple attackers. We evaluated our techniques through two test beds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings. Our experimental results show that our proposed methods can achieve over 90 percent Hit Rate and Precision when determining the number of attackers. Our localization results using a representative set of algorithms provide strong evidence of high accuracy of localizing multiple adversaries

IEEE 2013: EAACK: A Secure Intrusion-Detection System for MANETs

IEEE 2013 Transactions on Industrial Electronics

Abstract—The migration to wireless network from wired net-work has been a global trend in the past few decades. The mobility and scalability brought by wireless network made it possible in many applications. Among all the contemporary wireless net-works, Mobile Ad hoc NET work (MANET) is one of the most important and unique applications. On the contrary to traditional network architecture, MANET does not require a fixed network infrastructure; every single node works as both a transmitter and a receiver. Nodes communicate directly with each other when they are both within the same communication range. Otherwise, they rely on their neighbors to relay messages. The self-configuring ability of nodes in MANET made it popular among critical mission applications like military use or emergency recovery. However, the open medium and wide distribution of nodes make MANET vulnerable to malicious attackers. In this case, it is crucial to develop efficient intrusion-detection mechanisms to protect MANET from attacks. With the improvements of the technology and cut in hardware costs, we are witnessing a current trend of expanding MANETs into industrial applications. To adjust to such trend, we strongly believe that it is vital to address its potential security issues. In this paper, we propose and implement a new intrusion-detection system named Enhanced Adaptive ACKnowl-edgment (EAACK) specially designed for MANETs. Compared to contemporary approaches, EAACK demonstrates higher mali-cious-behavior-detection rates in certain circumstances while does not greatly affect the network performances.

IEEE 2013: EMAP: Expedite Message Authentication Protocol for Vehicular Ad Hoc Networks

IEEE 2013 Transactions on Mobile Computing

Abstract - Vehicular Ad Hoc Networks (VANETs) adopt the Public Key Infrastructure (PKI) and Certificate Revocation Lists (CRLs) for their security. In any PKI system, the authentication of a received message is performed by checking if the certificate of the sender is included in the current CRL, and verifying the authenticity of the certificate and signature of the sender. In this paper, we propose an Expedite Message Authentication Protocol (EMAP) for VANETs, which replaces the time-consuming CRL checking process by an efficient revocation checking process. The revocation check process in EMAP uses a keyed Hash Message Authentication Code (HMAC), where the key used in calculating the HMAC is shared only between non-revoked On-Board Units (OBUs). In addition, EMAP uses a novel probabilistic key distribution, which enables non-revoked OBUs to securely share and update a secret key. EMAP can significantly decrease the message loss ratio due to the message verification delay compared with the conventional authentication methods employing CRL. By conducting security analysis and performance evaluation, EMAP is demonstrated to be secure and efficient. Index Terms - Vehicular networks, Communication security, Message authentication, Certificate revocation.

IEEE 2013: Community-Aware Opportunistic Routing in Mobile Social Networks

IEEE 2013 Transactions on Computers

Abstract—Mobile social networks (MSNs) are a kind of delay tolerant network that consists of lots of mobile nodes with social characteristics. Recently, many social-aware algorithms have been proposed to address routing problems in MSNs. However, these algorithms tend to forward messages to the nodes with locally optimal social characteristics, and thus cannot achieve the optimal performance. In this paper, we propose a distributed optimal Community-Aware Opportunistic Routing (CAOR) algorithm. Our main contributions are that we propose a home-aware community model, whereby we turn an MSN into a network that only includes community homes. We prove that, in the network of community homes, we still can compute the minimum expected delivery delays of nodes through a reverse Dijkstra algorithm and achieve the optimal opportunistic routing performance. Since the number of communities is far less than the number of nodes in magnitude, the computational cost and maintenance cost for contact information are greatly reduced. We demonstrate how our algorithm significantly out performs the previous ones through extensive simulations, based on a real MSN trace and a synthetic MSN trace.

IEEE 2013: Redundancy Management of Multipath Routing for Intrusion Tolerance in Heterogeneous Wireless Sensor Networks

IEEE 2013 Transactions on Network and Service Management

Abstract—In this paper we propose redundancy management of heterogeneous wireless sensor networks (HWSNs), utilizing multipath routing to answer user queries in the presence of unreliable and malicious nodes. The ke concept of our redundancy management is to exploit the tradeoff between energy consumption vs. the gain in reliability, timeliness, and security to maximize the system useful lifetime. We formulate the tradeoff as an optimization problem for dynamically determining the best redundancy level to apply to multipath routing for intrusion tolerance so that the query response success probability is maximized while prolonging the useful lifetime. Furthermore, we consider this optimization problem for the case in which a voting-based distributed intrusion detection algorithm is applied to detect and evict malicious nodes in a HWSN. We develop a novel probability model to analyze the best redundancy level in terms of path redundancy and source redundancy, as well as the best intrusion detection settings in terms of the number of voters and the intrusion invocation interval under which the lifetime of a HWSN is maximized. We then apply the analysis results obtained to the design of a dynamic redundancy management algorithm to identify and apply the best design parameter settings at runtime in response to environment changes, to maximize the HWSN lifetime.

IEEE 2013: Optimizing Cloud Resources for Delivering IPTV Services through Virtualization

IEEE 2013 Transactions on Networking

Virtualized cloud-based services can take advantage of statistical multiplexing across applications to yield significant cost savings to the operator. However, achieving similar benefits with real-time services can be a challenge. In this paper, we seek to lower a provider’s costs of real-time IPTV services through a virtualized IPTV architecture and through intelligent time-shifting of service delivery. We take advantage of the differences in the deadlines associated with Live TV versus Video-on-Demand (VoD) to effectively multiplex these services. We provide a generalized framework for computing the amount of resources needed to support multiple services, without missing the deadline for any service. We construct the problem as an optimization formulation that uses a generic cost function. We consider multiple forms for the cost function (e.g., maximum, convex and concave functions) to reflect the different pricing options. The solution to this formulation gives the number of servers needed at different time instants to support these services. We implement a simple mechanism for time-shifting scheduled jobs in a simulator and study the reduction in server load using real traces from an operational IPTV network. Our results show that we are able to reduce the load by ∼ 24% (compared to a possible ∼ 31%). We also show that there are interesting open problems in designing mechanisms that allow time-shifting of load in such environments.

IEEE 2013: A Lightweight Encryption Scheme for Network-Coded Mobile Ad Hoc Networks

IEEE 2013 Transactions on Parallel and Distributed System

Energy saving is an important issue in Mobile Ad Hoc Networks (MANETs). Recent studies show that network coding can help reduce the energy consumption in MANETs by using less transmission. However, apart from transmission cost, there are other sources of energy consumption, e.g., data encryption/decryption. In this paper, we study how to leverage network coding to reduce the energy consumed by data encryption in MANETs. It is interesting that network coding has a nice property of intrinsic security, based on which encryption can be done quite efficiently. To this end, we propose P-Coding, a lightweight encryption scheme to provide confidentiality for network-coded MANETs in an energy-efficient way. The basic idea of P-Coding is to let the source randomly permutes the symbols of each packet (which is prefixed with its coding vector), before performing network coding operations. Without knowing the permutation, eavesdroppers cannot locate coding vectors for correct decoding, and thus cannot obtain any meaningful information. We demonstrate that due to its lightweight nature, P-Coding incurs minimal energy consumption compared to other encryption schemes.

IEEE 2013: Toward Privacy Preserving and Collusion Resistance in a Location Proof Updating System

IEEE 2013 Transactions on Mobile Computing
Today’s location-sensitive service relies on user’s mobile device to determine the current location. This allows malicious users to access a restricted resource or provide bogus alibis by cheating on their locations. To address this issue, we propose A Privacy-Preserving LocAtion proof Updating System (APPLAUS) in which colocated Bluetooth enabled mobile devices mutually generate location proofs and send updates to a location proof server. Periodically changed pseudonyms are used by the mobile devices to protect source location privacy from each other, and from the untrusted location proof server. We also develop user-centric location privacy model in which individual users evaluate their location privacy levels and decide whether and when to accept the location proof requests. In order to defend against colluding attacks, we also present betweenness ranking-based and correlation clustering-based approaches for outlier detection. APPLAUS can be implemented with existing network infrastructure, and can be easily deployed in Bluetooth enabled mobile devices with little computation or power cost. Extensive experimental results show that APPLAUS can effectively provide location proofs, significantly preserve the source location privacy, and effectively detect colluding attacks.

IEEE 2013: Optimal Multicast Capacity and Delay Tradeoffs in MANETs

IEEE 2013 Transactions on Mobile Computing

In this paper, we give a global perspective of multicast capacity and delay analysis in Mobile Ad Hoc Networks (MANETs). Specifically, we consider four node mobility models: two-dimensional i.i.d. mobility, wo-dimensional hybrid random walk, one-dimensional i.i.d. mobility, and one-dimensional hybrid random walk. Two mobility time-scales are investigated in this paper: Fast mobility where node mobility is at the same time-scale as data transmissions; Slow mobility where node mobility is assumed to occur at a much slower time-scale than data transmissions. Given a delay constraint D, we first characterize the optimal multicast capacity for each of the eight types of mobility models, and then we develop a scheme that can achieve a capacity-delay tradeoff close to the upper bound up to a logarithmic factor. In addition, we also study heterogeneous networks with infrastructure support.

IEEE 2013: NICE: Network Intrusion Detection and Countermeasure Selection in Virtual Network Systems

IEEE 2013 Transactions on Dependable and Secure Computing

Cloud security is one of most important issues that has attracted a lot of research and development effort in past few years. Particularly, attackers can explore vulnerabilities of a cloud system and compromise virtual machines to deploy further large-scale Distributed Denial-of-Service (DDoS). DDoS attacks usually involve early stage actions such as multistep exploitation, low-frequency vulnerability scanning, and compromising identified vulnerable virtual machines as zombies, and finally DDoS attacks through the compromised zombies. Within the cloud system, especially the Infrastructure-as-a-Service (IaaS) clouds, the detection of zombie exploration attacks is extremely difficult. This is because cloud users may install vulnerable applications on their virtual machines. To prevent vulnerable virtual machines from being compromised in the cloud, we propose a multiphase distributed vulnerability detection, measurement, and countermeasure selection mechanism called NICE, which is built on attack graph-based analytical models and reconfigurable virtual network-based countermeasures. The proposed framework leverages Open Flow network programming APIs to build a monitor and control plane over distributed programmable virtual switches to significantly improve attack detection and mitigate attack consequences. The system and security evaluations demonstrate the efficiency and effectiveness of the proposed solution

IEEE 2013: Participatory Privacy: Enabling Privacy in Participatory Sensing

IEEE 2013 Transactions on Networking

Participatory Sensing is an emerging computing paradigm that enables the distributed collection of data by self-selected participants. It allows the increasing number of mobile phone users to share local knowledge acquired by their sensor-equipped devices, e.g., to monitor temperature, pollution level or consumer pricing information. While research initiatives and prototypes proliferate, their real-world impact is often bounded to comprehensive user participation. If users have no incentive, or feel that their privacy might be endangered, it is likely that they will not participate. In this article, we focus on privacy protection in Participatory Sensing and introduce a suitable privacy-enhanced infrastructure. First, we provide a set of definitions of privacy requirements for both data producers (i.e., users providing sensed information) and consumers (i.e., applications accessing the data). Then, we propose an efficient solution designed for mobile phone users, which incurs very low overhead. Finally, we discuss a number of open problems and possible research directions

IEEE 2013: On Quality of Monitoring for Multi-channel Wireless Infrastructure Networks

IEEE 2013 Transactions on Mobile Computing

Passive monitoring utilizing distributed wireless sniffers is an effective technique to monitor activities in wireless infrastructure networks for fault diagnosis, resource management and critical path analysis. In this paper, we introduce a quality of monitoring (QoM) metric defined by the expected number of active users monitored, and investigate the problem of maximizing QoM by judiciously assigning sniffers to channels based on the knowledge of user activities in a multi-channel wireless network. Two types of capture models are considered. The user-centric model assumes frame-level capturing capability of sniffers such that the activities of different users can be distinguished while the sniffer-centric model only utilizes the binary channel information (active or not) at a sniffer. For the user-centric model, we show that the implied optimization problem is NP-hard, but a constant approximation ratio can be attained via polynomial complexity algorithms. For the sniffer-centric model, we devise stochastic inference schemes to transform the problem into the user-centric domain, where we are able to apply our polynomial approximation algorithms. The effectiveness of our proposed schemes and algorithms is further evaluated using both synthetic data as well as real-world traces from an operational WLAN.

IEEE 2013: SinkTrail: A Proactive Data Reporting Protocol for Wireless Sensor Networks

IEEE 2013 Transactions on Computers

In large-scale wireless sensor networks, leveraging data sinks’ mobility for data gathering has drawn substantial interests in recent years. Current researches either focus on planning a mobile sink’s moving trajectory in advance to achieve optimized network performance, or target at collecting a small portion of sensed data in the network. In many application scenarios, however, a mobile sink cannot move freely in the deployed area. Therefore, the per-calculated trajectories may not be applicable. To avoid constant sink location update traffics when a sink’s future locations cannot be scheduled in advance, we propose two energy-efficient proactive data reporting protocols, SinkTrail and SinkTrail-S, for mobile sink based data collection. The proposed protocols feature low-complexity and reduced control overheads. Two unique aspects distinguish our approach from previous ones we allow sufficient flexibility in the movement of mobile sinks to dynamically adapt to various terrestrial changes; and without requirements of GPS devices or predefined landmarks, SinkTrail establishes a logical coordinate system for routing and forwarding data packets, making it suitable for diverse application scenarios. We systematically analyze the impact of several design factors in the proposed algorithms. Both theoretical analysis and simulation results demonstrate that the proposed algorithms reduce control overheads and yield satisfactory
performance in finding shorter routing paths

IEEE 2013: Towards a Statistical Framework for Source Anonymity in Sensor Networks

IEEE 2013 Transactions on Mobile Computing

In certain applications, the locations of events reported by a sensor network need to remain anonymous. That is, unauthorized observers must be unable to detect the origin of such events by analyzing the network traffic. Known as the source anonymity problem, this problem has emerged as an important topic in the security of wireless sensor networks, with variety of techniques based on different adversarial assumptions being proposed. In this work, we present a new framework for modeling, analyzing and evaluating anonymity in sensor networks. The novelty of the proposed framework is twofold: first, it introduces the notion of “interval indistinguishably” and provides a quantitative measure to model anonymity in wireless sensor networks; second, it maps source anonymity to the statistical problem of binary hypothesis testing with nuisance parameters. We then analyze existing solutions for designing anonymous sensor networks using the proposed model. We show how mapping source anonymity to binary hypothesis testing with nuisance parameters leads to converting the problem of exposing private source information into searching for an appropriate data transformation that removes or minimize the effect of the nuisance information. By doing so, we transform the problem from analyzing real-valued sample points to binary codes, which opens the door for coding theory to be incorporated into the study of anonymous sensor networks. Finally, we discuss how existing solutions can be modified to improve their anonymity

IEEE 2013: Geo-Community-Based Broadcasting for Data Dissemination in Mobile Social Networks

IEEE 2013 Transactions on Parallel and Distributed System

IEEE 2013: Privacy-assured Outsourcing of Image Reconstruction Service in Cloud

IEEE 2013 Transaction on Emerging Topics in Computing

Large-scale image data sets are being exponentially generated today. Along with such data explosion is the fast growing trend to outsource the image management systems to the cloud for its abundant computing resources and benefits. However, how to protect the sensitive data while enabling outsourced image services becomes a major concern. To address these challenges, we propose OIRS, a novel outsourced image recovery service architecture, which exploits different domain technologies and takes security, efficiency, and design complexity into consideration from the very beginning of the service flow. Specifically, we choose to design OIRS under the compressed sensing (CS) framework, which is known for its simplicity of unifying the traditional sampling and compression for image acquisition. Data owners only need to outsource compressed image samples to cloud for reduced storage overhead. Besides, in OIRS, data users can harness the cloud to securely reconstruct images without revealing information from either the compressed image samples or the underlying image content. We start with the OIRS design for sparse data, which is the typical application scenario for compressed sensing, and then show its natural extension to the general data for meaningful tradeoffs between efficiency and accuracy. We thoroughly analyse the privacy-protection of OIRS and conduct extensive experiments to demonstrate the system effectiveness and efficiency. For completeness, we also discuss the expected performance speedup of OIRS through hardware built-in system design.

IEEE 2013 :Enabling Data Dynamic and Indirect Mutual Trust for Cloud Computing Storage Systems

IEEE 2013 Transaction on Parallel and Distributed Systems

Currently, the amount of sensitive data produced by many organizations is outpacing their storage ability. The management of such huge amount of data is quite expensive due to the requirements of high storage capacity and qualified personnel. Storage-as-a-Service (SaaS) offered by cloud service providers (CSPs) is a paid facility that enables organizations to outsource their data to be stored on remote servers. Thus, SaaS reduces the maintenance cost and mitigates the burden of large local data storage at the organization’s end. A data owner pays for a desired level of security and must get some compensation in case of any misbehavior committed by the CSP. On the other hand, the CSP needs a protection from any false accusation that may be claimed by the owner to get illegal compensations. In this paper, we propose a cloud-based storage scheme that allows the data owner to benefit from the facilities offered by the CSP and enables indirect mutual trust between them. The proposed scheme has four important features: it allows the owner to outsource sensitive data to a CSP, and perform full block-level dynamic operations on the outsourced data, i.e., block modification, insertion, deletion, and append, it ensures that authorized users (i.e., those who have the right to access the owner’s file) receive the latest version of the outsourced data, it enables indirect mutual trust between the owner and the CSP, and it allows the owner to grant or revoke access to the outsourced data. We discuss the security issues of the proposed scheme. Besides, we justify its performance through theoretical analysis and experimental evaluation of storage, communication, and computation overheads.

IEEE 2013 :Attribute-Based Encryption with Verifiable Outsourced Decryption

IEEE 2013 Transactions on Information Forensics and Security

Attribute-based encryption (ABE) is a public-key-based one-to-many encryption that allows users to encrypt and decrypt data based on user attributes. A promising application of ABE is flexible access control of encrypted data stored in the cloud, using access polices and ascribed attributes associated with private keys and cipher texts. One of the main efficiency drawbacks of the existing ABE schemes is that decryption involves expensive pairing operations and the number of such operations grows with the complexity of the access policy. Recently, Greenetal. proposed an ABE system with outsourced decryption that largely elimi-nates the decryption overhead for users. In such a system, a user provides an un trusted server, say a cloud service provider, with a transformation key that allows the cloud to translate any ABE cipher text satisfied by that user’s attributes or access policy into a simple cipher text, and it only incurs a small computational over-head for the user to recover the plain text from the transformed cipher text. Security of an ABE system with outsourced decryption ensures that an adversary (including a malicious cloud) will not be able to learn anything about the encrypted message; however, it does not guarantee the correctness of the transformation done by the cloud. In this paper, we consider a new requirement of ABE with outsourced decryption: verifiability. Informally, verifiability guarantees that a user can efficiently check if the transformation is done correctly. We give the formal model of ABE with verifiable outsourced decryption and propose a concrete scheme. We prove that our new scheme is both secure and verifiable, without relying on random oracles. Finally, we show an implementation of our

IEEE 2013: Towards Differential Query Services in Cost-Efficient Clouds

IEEE 2013 Transactions on Parallel and Distributed Systems

Cloud computing as an emerging technology trend is expected to reshape the advances in information technology. In a cost-efficient cloud environment, a user can tolerate a certain degree of delay while retrieving information from the cloud to reduce costs. In this paper, we address two fundamental issues in such an environment: privacy and efficiency. We first review a private keyword-based file retrieval scheme that was originally proposed by Ostrovsky. Their scheme allows a user to retrieve files of interest from an un trusted server without leaking any information. The main drawback is that it will cause a heavy querying overhead incurred on the cloud, and thus goes against the original intention of cost efficiency. In this paper, we present a scheme, termed efficient information retrieval for ranked query (EIRQ), based on an aggregation and distribution layer (ADL), to reduce querying overhead incurred on the cloud. In EIRQ, queries are classified into multiple ranks, where a higher ranked query can retrieve a higher percentage of matched files. A user can retrieve files on demand by choosing queries of different ranks. This feature is useful when there are a large number of matched files, but the user only needs a small subset of them. Under different parameter settings, extensive evaluations have been conducted on both analytical models and on a real cloud environment, in order to examine the effectiveness of our schemes.

IEEE 2013: EMAP: Expedite Message Authentication Protocol for Vehicular Ad Hoc Networks

IEEE 2013 Transactions on Mobile Computing

Abstract - Vehicular Ad Hoc Networks (VANETs) adopt the Public Key Infrastructure (PKI) and Certificate Revocation Lists (CRLs) for their security. In any PKI system, the authentication of a received message is performed by checking if the certificate of the sender is included in the current CRL, and verifying the authenticity of the certificate and signature of the sender. In this paper, we propose an Expedite Message Authentication Protocol (EMAP) for VANETs, which replaces the time-consuming CRL checking process by an efficient revocation checking process. The revocation check process in EMAP uses a keyed Hash Message Authentication Code (HMAC), where the key used in calculating the HMAC is shared only between non-revoked On-Board Units (OBUs). In addition, EMAP uses a novel probabilistic key distribution, which enables non-revoked OBUs to securely share and update a secret key. EMAP can significantly decrease the message loss ratio due to the message verification delay compared with the conventional authentication methods employing CRL. By conducting security analysis and performance evaluation, EMAP is demonstrated to be secure and efficient.

IEEE 2013: CLOUD COMPUTING FOR MOBILE USERS: CAN OFFLOADING COMPUTATION SAVE ENERGY?

IEEE 2013 TRANSACTIONS ON CLOUD COMPUTING

Cloud computing1 is a new paradigm in which computing resources such as processing, memory, and storage are not physically pres-ent at the user’s location. Instead, a service provider owns and manages these resources, and users access them via the Internet. For example, Amazon Web Services lets users store personal data via its Simple Storage Service (S3) and perform computations on stored data using the Elastic Compute Cloud (EC2). This type of computing provides many advantages for businesses—including low initial capital investment, shorter start-up time for new services, lower maintenance and operation costs, higher utilization through virtual-ization, and easier disaster recovery—that make cloud computing an attractive option. Reports suggest that there are several benefits in shifting computing from the desktop to the cloud.1,2 What about cloud computing for mobile users? The primary constraints for mobile computing are limited energy and wireless bandwidth. Cloud computing can provide energy savings as a service to mobile users, though it also poses some unique challenges.

IEEE 2013:CloudMoV: Cloud-based Mobile Social TV

IEEE 2013 TRANSACTIONS ON MULTIMEDIA

Abstract—The rapidly increasing power of personal mobile devices (smart phones, tablets, etc.) is providing much richer contents and social interactions to users on the move. This trend however is throttled by the limited battery lifetime of mobile devices and unstable wireless connectivity, making the highest possible quality of service experienced by mobile users not feasible. The recent cloud computing technology, with its rich resources to compensate for the limitations of mobile devices and connections, can potentially provide an ideal platform to support the desired mobile services. Tough challenges arise on how to effectively exploit cloud resources to facilitate mobile services, especially those with stringent interaction delay requirements. In this paper, we propose the design of a Cloud-based, novel Mobile social tV system (CloudMoV). The system effectively utilizes both PaaS (Platform-as-a-Service) and IaaS (Infrastructure-asa- Service) cloud services to offer the living-room experience of video watching to a group of disparate mobile users who can interact socially while sharing the video. To guarantee good streaming quality as experienced by the mobile users with time varying wireless connectivity, we employ a surrogate for each user in the IaaS cloud for video downloading and social exchanges on behalf of the user. The surrogate performs efficient stream trans coding that matches the current connectivity quality of the mobile user. Given the battery life as a key performance bottleneck, we advocate the use of burst transmission from the surrogates to the mobile users, and carefully decide the burst size which can lead to high energy efficiency and streaming quality. Social interactions among the users, in terms of spontaneous textual exchanges, are effectively achieved by efficient designs of data storage with BigTable and dynamic handling of large volumes of concurrent messages in a typical PaaS cloud. These various designs for flexible trans coding capabilities, battery efficiency of mobile devices and spontaneous social interactivity together provide an ideal platform for mobile social TV services. We have implemented CloudMoV on Amazon EC2 and Google App Engine and verified its superior performance based on real world experiments.

IEEE 2013: On Quality of Monitoring for Multi-channel Wireless Infrastructure Networks

IEEE 2013 TRANSACTION ON MOBILE COMPUTING

Abstract—Passive monitoring utilizing distributed wireless sniffers is an effective technique to monitor activities in wireless infrastructure networks for fault diagnosis, resource management and critical path analysis. In this paper, we introduce a quality of monitoring (QoM) metric defined by the expected number of active users monitored, and investigate the problem of maximizing QoM by judiciously assigning sniffers to channels based on the knowledge of user activities in a multi-channel wireless network. Two types of capture models are considered. The user-centric model assumes frame-level capturing capability of sniffers such that the activities of different users can be distinguished while the sniffer-centric model only utilizes the binary channel information (active or not) at a sniffer. For the user-centric model, we show that the implied optimization problem is NP-hard, but a constant approximation ratio can be attained via polynomial complexity algorithms. For the sniffer-centric model, we devise stochastic inference schemes to transform the problem into the user-centric domain, where we are able to apply our polynomial approximation algorithms. The effectiveness of our proposed schemes and algorithms is further evaluated using both synthetic data as well as real-world traces from an operational WLAN.

IEEE 2013: Optimal Multicast Capacity and Delay Tradeoffs in MANETs

IEEE 2013 TRANSACTIONS ON MOBILE COMPUTING

Abstract—In this paper, we give a global perspective of multicast capacity and delay analysis in Mobile Ad Hoc Networks (MANETs). Specifically, we consider four node mobility models: two-dimensional i.i.d. mobility, two-dimensional hybrid random walk, one-dimensional i.i.d. mobility, and one-dimensional hybrid random walk. Two mobility time-scales are investigated in this paper: Fast mobility where node mobility is at the same time-scale as data transmissions; Slow mobility where node mobility is assumed to occur at a much slower time-scale than data transmissions. Given a delay constraint D, we first characterize the optimal multicast capacity for each of the eight types of mobility models, and then we develop a scheme that can achieve a capacity-delay tradeoff close to the upper bound up to a logarithmic factor. In addition, we also study heterogeneous networks with infrastructure support.

IEEE 2013 :DCIM: Distributed Cache Invalidation Method for Maintaining Cache Consistency in Wireless Mobile Networks

IEEE 2013 Transactions on Mobile Computing

IEEE 2013: Generation of Personalized Ontology Based on Consumer Emotion and Behavior Analysis

IEEE 2013 Transactions on Affective Computing

Abstract—The relationships between consumer emotions and their buying behaviors have been well documented. Technology-savvy consumers often use the web to find information on products and services before they commit to buying. We propose a semantic web usage mining approach for discovering periodic web access patterns from annotated web usage logs which incorporates information on consumer emotions and behaviors through self-reporting and behavioral tracking. We use fuzzy logic to represent real-life temporal concepts (e.g., morning) and requested resource attributes (ontological domain concepts for the requested URLs) of periodic pattern-based web access activities. These fuzzy temporal and resource representations, which contain both behavioral and emotional cues, are incorporated into a Personal Web Usage Lattice that models the user’s web access activities. From this, we generate a Personal Web Usage Ontology written in OWL, which enables semantic web applications such as personalized web resources recommendation. Finally, we demonstrate the effectiveness of our approach by presenting experimental results in the context of personalized web resources recommendation with varying degrees of emotional influence. Emotional influence has been found to contribute positively to adaptation in personalized recommendation.

IEEE 2013: Winds of Change: From Vendor Lock-In to the Meta Cloud

IEEE 2013 Transactions on Internet Computing

Abstract—The cloud computing paradigm has achieved widespread adoption in recent years. Its success is due largely to customers’ ability to use services on demand with a pay-as-you go pricing model, which has proved convenient in many respects. Low costs and high flexibility make migrating to the cloud compelling. Despite its obvious advantages, however, many com-panies hesitate to “move to the cloud,” mainly because of concerns related to service availability, data lock-in, and legal uncertainties. Lock-in is particularly problematic. For one thing, even though public cloud availability is gener-ally high, outages still occur. Businesses locked into such a cloud are Essentially at a standstill until the cloud is back online. Moreover, public cloud providers generally don’t guarantee par-ticular service level agreements (SLAs) that are; businesses locked into a cloud have no guaran-tees that it will continue to provide the required quality of service (QoS). Finally, most public cloud providers’ terms of service let that provider unilaterally change pricing at any time. Hence, a business locked into a cloud has no mid- or long-term control over its own IT costs

IEEE 2013:Toward a reliable, secure and fault tolerant smart grid state estimation in the cloud

IEEE 2013 Transactions on Innovative Smart Grid Technologies

Abstract—the collection and prompt analysis of synchropha-sor measurements is a key step towards enabling the future smart power grid, in which grid management applications would be deployed to monitor and react intelligently to changing conditions. The potential exists to slash inefficiencies and to adaptively reconfigure the grid to take better advantage of renewable, coordinate and share reactive power, and to re-duce the risk of catastrophic large-scale outages. However, to realize this potential, a number of technical challenges must be overcome. We describe a continuously active, timely monitoring framework that we have created, architected to support a wide range of grid-control applications in a standard manner designed to leverage cloud computing. Cloud computing systems bring significant advantages, including an elastic, highly available and cost-effective compute infrastructure well-suited for this application. We believe that by showing how challenges of reliability, timeliness, and security can be addressed while leveraging cloud standards, our work opens the door for wider exploitation of the cloud by the smart grid community. This paper characterizes a PMU-based state- estimation application, explains how the desired system maps to a cloud architecture, identifies limitations in the standard cloud infrastructure relative to the needs of this use-case, and then shows how we adapt the basic cloud platform options with sophisticated technologies of our own to achieve the required levels of usability, fault tolerance, and parallelism

IEEE 2013: Security and Privacy Enhancing Multi-Cloud Architectures

IEEE 2013 Transactions on Dependable and Secure Computing

Abstract—Security challenges are still amongst the biggest obstacles when considering the adoption of cloud services. This triggered a lot of research activities, resulting in a quantity of proposals targeting the various cloud security threats. Alongside with these security issues the cloud paradigm comes with a new set of unique features which open the path towards novel security approaches, techniques and architectures. This paper provides a survey on the achievable security merits by making use of multiple distinct clouds simultaneously. Various distinct architectures are introduced and discussed according to their security and privacy capabilities and prospects.

IEEE 2013: Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute-based Encryption

IEEE 2013 Transactions on Parallel and Distributed Systems

Abstract—Personal health record (PHR) is an emerging patient-centric model of health information exchange, which is often outsourced to be stored at a third party, such as cloud providers. However, there have been wide privacy concerns as personal health information could be exposed to those third party servers and to unauthorized parties. To assure the patients’ control over access to their own PHRs, it is a promising method to encrypt the PHRs before outsourcing. Yet, issues such as risks of privacy exposure, scalability in key management, flexible access and efficient user revocation, have remained the most important challenges toward achieving fine-grained, cryptographically enforced data access control. In this paper, we propose a novel patient-centric framework and a suite of mechanisms for data access control to PHRs stored in semi-trusted servers. To achieve fine-grained and scalable data access control for PHRs, we leverage attribute based encryption (ABE) techniques to encrypt each patient’s PHR file. Different from previous works in secure data outsourcing, we focus on the multiple data owner scenario, and divide the users in the PHR system into multiple security domains that greatly reduces the key management complexity for owners and users. A high degree of patient privacy is guaranteed simultaneously by exploiting multi-authority ABE. Our scheme also enables dynamic codification of access policies or file attributes, supports efficient on-demand user/attribute revocation and break-glass access under emergency scenarios. Extensive analytical and experimental results are presented which show the security, scalability and efficiency of our proposed scheme

IEEE 2013: Govcloud: Using Cloud Computing in Public Organizations

IEEE 2013 Transactions on Technology and Society Magazine

Abstract: Governments are fac-ing reductions in ICT budgets just as users are increasing demands for electronic services. One solution announced aggressively by vendors is cloud computing. Cloud comput-ing is not a new technology, but as described by Jackson] is a new way of offering services, taking into consideration business and economic models for providing and consuming ICT services. Here we explain the impact and benefits for public organizations of cloud services and explore issues of why governments are slow to adopt use of the cloud. The exist-ing literature does not cover this subject in detail, especially for European organizations

IEEE 2013: Dynamic Resource Allocation using Virtual Machines for Cloud Computing Environment

IEEE 2013 Transactions on Parallel and Distributed Systems

Cloud computing allows business customers to scale up and down their resource usage based on needs. Many of the touted gains in the cloud model come from resource multiplexing through visualization technology. In this paper, we present a system that uses visualization technology to allocate data center resources dynamically based on application demands and support green computing by optimizing the number of servers in use. We introduce the concept of “skewness” to measure the unevenness in the multi-dimensional resource utilization of a server. By minimizing skewness, we can combine different types of workloads nicely and improve the overall utilization of server resources. We develop a set of heuristics that prevent overload in the system effectively while saving energy used. Trace driven simulation and experiment results demonstrate that our algorithm achieves good performance.

IEEE 2013: Privacy Preserving Delegated Access Control in Public Clouds

IEEE 2013 Transactions on Knowledge and Data Engineering

Abstract—Current approaches to enforce fine-grained access control on confidential data hosted in the cloud are based on fine-grained encryption of the data. Under such approaches, data owners are in charge of encrypting the data before uploading them on the cloud and re-encrypting the data whenever user credentials or authorization policies change. Data owners thus incur high communication and computation costs. A better approach should delegate the enforcement of fine-grained access control to the cloud, so to minimize the overhead at the data owners, while assuring data confidentiality from the cloud. We propose an approach, based on two layers of encryption, that addresses such requirement. Under our approach, the data owner performs a coarse-grained encryption, whereas the cloud performs a fine-grained encryption on top of the owner encrypted data. A challenging issue is how to decompose access control policies (ACPs) such that the two layer encryption can be performed. We show that this problem is NP-complete and propose novel optimization algorithms. We utilize an efficient group key management scheme that supports expressive ACPs. Our system assures the confidentiality of the data and preserves the privacy of users from the cloud while delegating most of the access control enforcement to the cloud.

IEEE 2013: Privacy-Preserving Public Auditing for Secure Cloud Storage

IEEE 2013 TRANSACTIONS ON CLOUD COMPUTING

Abstract—Using Cloud Storage, users can remotely store their data and enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources, without the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the outsourced data makes the data integrity protection in Cloud Computing a formidable task, especially for users with constrained computing resources. Moreover, users should be able to just use the cloud storage as if it is local, without worrying about the need to verify its integrity. Thus, enabling public audit ability for cloud storage is of critical importance so that users can resort to a third party auditor (TPA) to check the integrity of outsourced data and be worry-free. To securely introduce an effective TPA, the auditing process should bring in no new vulnerabilities towards user data privacy, and introduce no additional online burden to user. In this paper, we propose a secure cloud storage system supporting privacy-preserving public auditing. We further extend our result to enable the TPA to perform audits for multiple users simultaneously and efficiently. Extensive security and performance analysis show the proposed schemes are provably secure and highly efficient

IEEE 2013 : Load Re balancing for Distributed File Systems in Clouds

IEEE 2013 Transactions on Parallel and Distributed Systems

Abstract—Distributed file systems are key building blocks for cloud computing applications based on the Map Reduce programming paradigm. In such file systems, nodes simultaneously serve computing and storage functions; a file is partitioned into a number of chunks allocated in distinct nodes so that Map Reduce tasks can be performed in parallel over the nodes. However, in a cloud computing environment, failure is the norm, and nodes may be upgraded, replaced, and added in the system. Files can also be dynamically created, deleted, and appended. This results in load imbalance in a distributed file system; that is, the file chunks are not distributed as uniformly as possible among the nodes. Emerging distributed file systems in production systems strongly depend on a central node for chunk reallocation. This dependence is clearly inadequate in a large-scale, failure-prone environment because the central load balance is put under considerable workload that is linearly scaled with the system size, and may thus become the performance bottleneck and the single point of failure. In this paper, a fully distributed load re balancing algorithm is presented to cope with the load imbalance problem. Our algorithm is compared against a centralized approach in a production system and a competing distributed solution presented in the literature. The simulation results indicate that our proposal is comparable with the existing centralized approach and considerably outperforms the prior distributed algorithm in terms of load imbalance factor, movement cost, and algorithmic overhead. The performance of our proposal implemented in the Hadoop distributed file system is further investigated in a cluster environment.

IEEE 2013: A Load Balancing Model Based on Cloud Partitioning for the Public Cloud

IEEE 2013 TRANSACTIONS ON CLOUD COMPUTING

Abstract: Load balancing in the cloud computing environment has an important impact on the performance. Good load balancing makes cloud computing more efficient and improves user satisfaction. This article introduces a better load balance model for the public cloud based on the cloud partitioning concept with a switch mechanism to choose different strategies for different situations. The algorithm applies the game theory to the load balancing strategy to improve the efficiency in the public cloud environment.

IEEE 2013: SPOC: A Secure and Privacy-preserving Opportunistic Computing Framework for Mobile-Healthcare Emergency

IEEE 2013 Transactions on Parallel and Distributed Systems

Abstract—With the pervasiveness of smart phones and the advance of wireless body sensor networks (BSNs), mobile Healthcare (m-Healthcare), which extends the operation of Healthcare provider into a pervasive environment for better health monitoring, has attracted considerable interest recently. However, the flourish of m-Healthcare still faces many challenges including information security and privacy preservation. In this paper, we propose a secure and privacy-preserving opportunistic computing framework, called SPOC, for m-Healthcare emergency. With SPOC, smart phone resources including computing power and energy can be opportunistically gathered to process the computing-intensive personal health information (PHI) during m-Healthcare emergency with minimal privacy disclosure. In specific, to leverage the PHI privacy disclosure and the high reliability of PHI process and transmission in m-Healthcare emergency, we introduce an efficient user-centric privacy access control in SPOC framework, which is based on an attribute-based access control and a new privacy-preserving scalar product computation (PPSPC) technique, and allows a medical user to decide who can participate in the opportunistic computing to assist in processing his overwhelming PHI data. Detailed security analysis shows that the proposed SPOC framework can efficiently achieve user-centric privacy access control in m-Healthcare emergency. In addition, performance evaluations via extensive simulations demonstrate the SPOC’s effectiveness in term of providing high reliable PHI process and transmission while minimizing the privacy disclosure during m-Healthcare emergency.

IEEE 2013: Vampire Attacks: Draining Life from Wireless Ad Hoc Sensor Networks

IEEE 2013 Transaction on Mobile Computing

Technology - Available in Java & .Net

Abstract— Ad hoc low-power wireless networks are an exciting research direction in sensing and pervasive computing. Prior security work in this area has focused primarily on denial of communication at the routing or medium access control levels. This paper explores resource depletion attacks at the routing protocol layer, which permanently disable networks by quickly draining nodes' battery power. These "Vampire” attacks are not specific to any specific protocol, but rather rely on the properties of many popular classes of routing protocols. We find that all examined protocols are susceptible to Vampire attacks, which are devastating, difficult to detect, and are easy to carry out using as few as one malicious insider sending only protocol-compliant messages. In the worst case, a single Vampire can increase network-wide energy usage by a factor of O(N), where N in the number of network nodes. We discuss methods to mitigate these types of attacks, including a new proof-of-concept protocol that provably bounds the damage caused by Vampires during the packet forwarding phase.

IEEE 2012: Expert Discovery and Interactions in Mixed Service-Oriented Systems

IEEE 2012 TRANSACTIONS ON SERVICES COMPUTING

Abstract— Web-based collaborations and processes have become essential in today’s business environments. Such processes typically span interactions between people and services across globally distributed companies. Web services and SOA are the defacto technology to implement compositions of humans and services. The increasing complexity of compositions and the distribution of people and services require adaptive and context-aware interaction models. To support complex interaction scenarios, we introduce a mixed service-oriented system composed of both human-provided and software-based services interacting to perform joint activities or to solve emerging problems. However, competencies of people evolve over time, thereby requiring approaches for the automated management of actor skills, reputation, and trust. Discovering the right actor in mixed service-oriented systems is challenging due to scale and temporary nature of collaborations. We present a novel approach addressing the need for flexible involvement of experts and knowledge workers in distributed collaborations. We argue that the automated inference of trust between members is a key factor for successful collaborations. Instead of following a security perspective on trust, we focus on dynamic trust in collaborative networks. We discuss Human-Provided Services (HPS) and an approach for managing user preferences and network structures. HPS allows experts to offer their skills and capabilities as services that can be requested on demand. Our main contributions center around a context-sensitive trust-based algorithm called Expert HITS inspired by the concept of hubs and authorities in Web-based environments. Expert HITS takes trust-relations and link properties in social networks into account to estimate the reputation of users.

IEEE 2012 Cooperative Download in Vehicular Environments

Abstract—We consider a complex (i.e., non-linear) road scenario where users aboard vehicles equipped with communication interfaces are interested in downloading large files from road-side Access Points (APs). We investigate the possibility of exploiting opportunistic encounters among mobile nodes so to augment the transfer rate experienced by vehicular downloaders. To that end, we devise solutions for the selection of carriers and data chunks at the APs, and evaluate them in real-world road topologies, under different AP deployment strategies. Through extensive simulations, we show that carry & forward transfers can significantly increase the download rate of vehicular users in urban/suburban environments, and that such a result holds throughout diverse mobility scenarios, AP placements and network loads.

IEEE 2012 Privacy and Integrity Preserving Range Queries in Sensor Networks

Abstract—The architecture of two-tiered sensor networks, where storage nodes serve as an intermediate tier between sensors and a sink for storing data and processing queries, has been widely adopted because of the benefits of power and storage saving for sensors as well as the efficiency of query processing. However, the importance of storage nodes also makes them attractive to attackers. In this paper, we propose SafeQ, a protocol that prevents attackers from gaining information from both sensor collected data and sink issued queries. SafeQ also allows a sink to detect compromised storage nodes when they misbehave. To preserve privacy, SafeQ uses a novel technique to encode both data and queries such that a storage node can correctly process encoded queries over encoded data without knowing their values. To preserve integrity, we propose two schemes—one using Merkle hash trees and another using a new data structure called neighborhood chains—to generate integrity verification information so that a sink can use this information to verify whether the result of a query contains exactly the data items that satisfy the query. To improve performance, we propose an optimization technique using Bloom filters to reduce the communication cost between sensors and storage nodes.

IEEE 2012: Privacy-Preserving Multi-keyword Ranked Search over Encrypted Cloud Data

Abstract— With the advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in cloud, it is crucial for the search service to allow multi-keyword query and provide result similarity ranking to meet the effective data retrieval need. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely differentiate the search results. In this paper, for the first time, we define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. Among various multi-keyword semantics, we choose the efficient principle of “coordinate matching”, i.e., as many matches as possible, to capture the similarity between search query and data documents, and further use “inner product similarity” to quantitatively formalize such principle for similarity measurement. We first propose a basic MRSE scheme using secure inner product computation, and then significantly improve it to meet different privacy requirements in two levels of threat models. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given, and experiments on the real-world dataset further show proposed schemes indeed introduce low overhead on computation and communication.

IEEE 2012: Ensuring Distributed Accountability for Data Sharing in the Cloud

IEEE 2012 TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING

Abstract— Cloud computing enables highly scalable services to be easily consumed over the Internet on an as-needed basis. A major feature of the cloud services is that users’ data are usually processed remotely in unknown machines that users do not own or operate. While enjoying the convenience brought by this new emerging technology, users’ fears of losing control of their own data (particularly, financial and health data) can become a significant barrier to the wide adoption of cloud services. To address this problem, in this paper, we propose a novel highly decentralized information accountability framework to keep track of the actual usage of the users’ data in the cloud. In particular, we propose an object-centered approach that enables enclosing our logging mechanism together with users’ data and policies. We leverage the JAR programmable capabilities to both create a dynamic and traveling object, and to ensure that any access to users’ data will trigger authentication and automated logging local to the JARs. To strengthen user’s control, we also provide distributed auditing mechanisms. We provide extensive experimental studies that demonstrate the efficiency and effectiveness of the proposed approaches.

IEEE 2012: Towards Secure and Dependable Storage Services in Cloud Computing

Abstract— Cloud storage enables users to remotely store their data and enjoy the on-demand high quality cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a service is also relinquishing users’ physical possession of their outsourced data, which inevitably poses new security risks towards the correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable cloud storage service, we propose in this paper a flexible distributed storage integrity auditing mechanism, utilizing the homomorphic token and distributed erasure-coded data. The proposed design allows users to audit the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design further supports secure and efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks

IEEE 2012:A Secure Intrusion detection system against DDOS attack in Wireless Mobile Ad-hoc Network

IEEE 2012 INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS

Abstract— Wireless Mobile ad-hoc network (MANET) is an emerging technology and have great strength to be applied in critical situations like battlefields and commercial applications such as building, traffic surveillance, MANET is infrastructure less, with no any centralized controller exist and also each node contain routing capability, Each device in a MANET is independently free to move in any direction, and will therefore change its connections to other devices frequently. So one of the major challenges wireless mobile ad-hoc networks face today is security, because no central controller exists. MANETs are a kind of wireless ad hoc networks that usually has a routable networking environment on top of a link layer ad hoc network. Ad hoc also contains wireless sensor network so the problems is facing by sensor network is also faced by MANET. While developing the sensor nodes in unattended environment increases the chances of various attacks. There are many security attacks in MANET and DDoS (Distributed denial of service) is one of them. Our main aim is seeing the effect of DDoS in routing load, packet drop rate, end to end delay, i.e. maximizing due to attack on network. And with these parameters and many more also we build secure IDS to detect this kind of attack and block it. In this paper we discussed some attacks on MANET and DDOS also and provide the security against the DDOS attack.

IEEE 2012: HASBE: A Hierarchical Attribute-Based Solution for Flexible and Scalable Access Control

in Cloud Computing

IEEE 2012 TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY

Abstract— Cloud computing has emerged as one of the most influential paradigms in the IT industry in recent years. Since this new computing technology requires users to entrust their valuable data to cloud providers, there have been increasing security and privacy concerns on outsourced data. Several schemes employing attribute-based encryption (ABE) have been proposed for access control of outsourced data in cloud computing; however, most of them suffer from inflexibility in implementing complex access control policies. In order to realize scalable, flexible, and fine-grained access control of outsourced data in cloud computing, in this paper, we propose hierarchical attribute-set-based encryption (HASBE) by extending cipher text-policy attribute-set-based encryption (ASBE) with a hierarchical structure of users. The proposed scheme not only achieves scalability due to its hierarchical structure, but also inherits flexibility and fine-grained access control in supporting compound attributes of ASBE. In addition, HASBE employs multiple value assignments for access expiration time to deal with user revocation more efficiently than existing schemes. We formally prove the security of HASBE based on security of the cipher text-policy attribute-based encryption (CP-ABE) scheme by Bettencourt et al. and analyze its performance and computational complexity. We implement our scheme and show that it is both efficient and flexible in dealing with access control for outsourced data in cloud computing with comprehensive experiments.

IEEE 2012: A Keyless Approach to Image Encryption

IEEE 2012 COMMUNICATION SYSTEMS AND NETWORK TECHNOLOGIES

Abstract— Maintaining the secrecy and confidentiality of images is a vibrant area of research, with two different approaches being followed, the first being encrypting the images through encryption algorithms using keys, the other approach involves dividing the image into random shares to maintain the images secrecy. Unfortunately heavy computation cost and key management limit the employment of the first approach and the poor quality of the recovered image from the random shares limit the applications of the second approach. In this paper we propose a novel approach without the use of encryption keys. The approach employs Sieving, Division and Shuffling to generate random shares such that with minimal computation, the original secret image can be recovered from the random shares without any loss of image quality.

IEEE 2012: Separable Reversible Data Hiding in Encrypted Image

IEEE 2012 TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY

Abstract— This work proposes a novel scheme for separable reversible data hiding in encrypted images. In the first phase, a content owner encrypts the original uncompressed image using an encryption key. Then, a data-hider may compress the least significant bits of the encrypted image using a data-hiding key to create a sparse space to accommodate some additional data. With an encrypted image containing additional data, if a receiver has the data-hiding key, he can extract the additional data though he does not know the image content. If the receiver has the encryption key, he can decrypt the received data to obtain an image similar to the original one, but cannot extract the additional data. If the receiver has both the data-hiding key and the encryption key, he can extract the additional data and recover the original content without any error by exploiting the spatial correlation in natural image when the amount of additional data is not too large.

IEEE 2012:The Future of Cloud-Based Entertainment

IEEE 2012 JOURNALS & MAGAZINES

Abstract— This paper notes some signification trends related to the Internet and Becloud computing that will change the way entertainment is delivered and experienced. After extrapolating some general conclusions from these trends, two scenarios are described to illustrate predicted entertainment experiences.

IEEE 2012: AMPLE: An Adaptive Traffic Engineering System Based on Virtual Routing Topologies

IEEE 2012 COMMUNICATIONS MAGAZINE

Abstract— Handling traffic dynamics in order to avoid network congestion and subsequent service disruptions is one of the key tasks performed by contemporary network management systems. Given the simple but rigid routing and forwarding functionalities in IP base environments, efficient resource management and control solutions against dynamic traffic conditions is still yet to be obtained. In this article, we introduce AMPLE — an efficient traffic engineering and management system that performs adaptive traffic control by using multiple virtualized routing topologies. The proposed system consists of two compel monetary components: offline link weight optimization that takes as input the physical network topology and tries to produce maximum routing path diversity across multiple virtual routing topologies for long term operation through the optimized setting of link weights. Based on these diverse paths, adaptive traffic control performs intelligent traffic splitting across individual routing topologies in reaction to the monitored network dynamics at short timescale. According to our evaluation with real network topologies and traffic traces, the proposed system is able to cope almost optimally with unpredicted traffic dynamics and, as such, it constitutes a new proposal for achieving better quality of service and overall network performance in IP networks.

IEEE 2012:IEEE 2012: An Adaptive Opportunistic Routing Scheme for Wireless Ad-hoc Networks

IEEE 2012 NETWORKING

Abstract— In this paper, a distributed adaptive opportunistic routing scheme for multi-hop wireless ad-hoc networks is proposed. The proposed scheme utilizes a reinforcement learning framework to opportunistically route the packets even in the absence of reliable knowledge about channel statistics and network model. This scheme is shown to be optimal with respect to an expected average per packet reward criterion. The proposed routing scheme jointly addresses the issues of learning and routing in an opportunistic context, where the network structure is characterized by the transmission success probabilities. In particular, this learning framework leads to a stochastic routing scheme which optimally “explores” and “exploits” the opportunities in the network.

IEEE 2012:Topology Control In Mobile Ad Hoc Networks With Cooperative Communications

IEEE 2012 TRANSACTIONS ON WIRELESS COMMUNICATIONS

Abstract— Cooperative communication has received tremendous interest for wireless networks. Most existing works on cooperative communications are focused on link-level physical layer issues. Consequently, the impacts of cooperative communications on network-level upper layer issues, such as topology control, routing and network capacity, are largely ignored. In this article, we propose a Capacity-Optimized Cooperative (COCO) topology control scheme to improve the network capacity in MANETs by jointly considering both upper layer network capacity and physical layer cooperative communications. Through simulations, we show that physical layer cooperative communications have significant impacts on the network capacity, and the proposed topology control scheme can substantially improve the network capacity in MANETs with cooperative communications

IEEE 2012: Performance of PCN-Based Admission Control Under Challenging Conditions

IEEE 2012 TRANSACTIONS ON NETWORKING

Abstract— Precongistion notification (PCN) is a packet-marking technique for IP networks to notify egress nodes of a so-called PCN domain whether the traffic rate on some links exceeds certain configurable bounds. This feedback is used by decision points for admission control (AC) to block new flows when the traffic load is already high. PCN-based AC is simpler than other AC methods because interior routers do not need to keep per-flow states. Therefore, it is currently being standardized by the IETF. We discuss various realization options and analyze their performance in the presence of flash crowds or with multipath routing by means of simulation and mathematical modeling. Such situations can be aggravated by insufficient flow aggregation, long round-trip times, on/off traffic, delayed media, inappropriate marker configuration, and smoothed feedback

IEEE 2012: A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Abstract— The interest for data mining techniques has increased tremendously during the past decades, and numerous classification techniques have been applied in a wide range of business applications. Hence, the need for adequate performance measures has become more important than ever. In this paper, a cost benefit analysis framework is formalized in order to define performance measures which are aligned with the main objectives of the end users, i.e. profit maximization. A new performance measure is defined, the expected maximum profit criterion. This general framework is then applied to the customer churn problem with its particular cost benefit structure. The advantage of this approach is that it assists companies with selecting the classifier which maximizes the profit. Moreover, it aids with the practical implementation in the sense that it provides guidance about the fraction of the customer base to be included in the retention campaign.

IEEE 2012: Prediction of User’s Web-Browsing Behavior: Application of Markov Model

IEEE TRANSACTIONS ON SYSTEMSAUGUST 2012

Abstract— Web prediction is a classification problem in which we attempt to predict the next set of Web pages that a user may visit based on the knowledge of the previously visited pages. Predicting user’s behavior while serving the Internet can be applied effectively in various critical applications. Such application has traditional tradeoffs between modeling complexity and prediction accuracy. In this paper, we analyze and study Markov model and all-Kth Markov model in Web prediction. We propose a new modified Markov model to alleviate the issue of scalability in the number of paths. In addition, we present a new two-tier prediction framework that creates an example classifier EC, based on the training examples and the generated classifiers. We show that such framework can improve the prediction time without compromising Prediction accuracy. We have used standard benchmark data sets to analyze, compare, and demonstrate the effectiveness of our techniques using variations of Markov models and association rule mining. Our experiments show the effectiveness of our modified Markov model in reducing the number of paths without compromising accuracy. Additionally, the results support our analysis conclusions that accuracy improves with higher orders of all-Kth model.

IEEE 2012: Efficient audit service outsourcing for data integrity in clouds

IEEE 2012 Transactions on Cloud Computing

Abstract — Cloud-based outsourced storage relieves the client’s burden for storage management and maintenance by providing a comparably low-cost, scalable, location-independent platform. However, the fact that clients no longer have physical possession of data indicates that they are facing a potentially formidable risk for missing or corrupted data. To avoid the security risks, audit services are critical to ensure the integrity and availability of outsourced data and to achieve digital forensics and credibility on cloud computing. Provable data possession (PDP), which is a cryptographic technique for verifying the integrity of data without retrieving it at an untrusted server, can be used to realize audit services. In this paper, profiting from the interactive zero-knowledge proof system, we address the construction of an interactive PDP protocol to prevent the fraudulence of prover (soundness property) and the leakage of verified data (zero-knowledge property). We prove that our construction holds these properties based on the computation Diffie–Hellman assumption and the rewindable black-box knowledge extractor. We also propose an efficient mechanism with respect to probabilistic queries and periodic verification to reduce the audit costs per verification and implement abnormal detection timely. In addition, we present an efficient method for selecting an optimal parameter value to minimize computational overheads of cloud audit services. Our experimental results demonstrate the effectiveness of our approach.

IEEE 2012: Cloud Computing Security: From Single to Multi-Clouds

IEEE 2012 - 45th Hawaii International Conference on System Sciences

Abstract — The use of cloud computing has increased rapidly in many organizations. Cloud computing provides many benefits in terms of low cost and accessibility of data. Ensuring the security of cloud computing is a major factor in the cloud computing environment, as users often store sensitive information with cloud storage providers but these providers may be untrusted. Dealing with “single cloud” providers is predicted to become less popular with customers due to risks of service availability failure and the possibility of malicious insiders in the single cloud. A movement towards “multi-clouds”, or in other words,“interclouds” or “cloud-of-clouds” has emerged recently. This paper surveys recent research related to single and multi-cloud security and addresses possible solutions. It is found that the research into the use of multi-cloud providers to maintain security has received less attention from the research community than has the use of single clouds. This work aims to promote the use of multi-clouds due to its ability to reduce security risks that affect the cloud computing user.

IEEE 2012: Scalable and Secure Sharing of Personal Health Records in Cloud Computing using Attribute-based Encryption

IEEE 2012 TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS

Abstract— Personal health record (PHR) is an emerging patient-centric model of health information exchange, which is often outsourced to be stored at a third party, such as cloud providers. However, there have been wide privacy concerns as personal health information could be exposed to those third party servers and to unauthorized parties. To assure the patients’ control over access to their own PHRs, it is a promising method to encrypt the PHRs before outsourcing. Yet, issues such as risks of privacy exposure, scalability in key management, flexible access and efficient user revocation, have remained the most important challenges toward achieving fine-grained, photographically enforced data access control. In this paper, we propose a novel patient-centric framework and a suite of mechanisms for data access control to PHRs stored in semi-trusted servers. To achieve fine-grained and scalable data access control for PHRs, we leverage attribute based encryption (ABE) techniques to encrypt each patient’s PHR file. Different from previous works in secure data outsourcing, we focus on the multiple data owner scenario, and divide the users in the PHR system into multiple security domains that greatly reduces the key management complexity for owners and users. A high degree of patient privacy is guaranteed simultaneously by exploiting multi-authority ABE. Our scheme also enables dynamic modification of access policies or file attributes, supports efficient on-demand user/attribute revocation and break-glass access under emergency scenarios. Extensive analytically and experimental results are presented which show the security, scalability and efficiency of our proposed scheme.

IEEE 2012: Access Control Mechanisms for Outsourced Data in Cloud

IEEE COMMUNICATION SYSTEMS AND NETWORKS (COMSNETS), 2012

Abstract— Cloud computing poses new security and access control challenges as the users outsource their sensitive data onto cloud storage. The outsourced data should be protected from unauthorized users access including the honest-but-curious cloud servers those hosts the data. In this paper, we propose two access control mechanisms based on (1) Polynomial interpolation technique and (2) Multi linear map. In these schemes, the authorized user need to store only a single key material irrespective of number of data items to which he has authorized access.

IEEE 2012: Horizontal Aggregations in SQL to Prepare Data Sets for Data Mining Analysis

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, APRIL 2012

Abstract— Preparing a data set for analysis is generally the most time consuming task in a data mining project, requiring many complex SQL queries, joining tables, and aggregating columns. Existing SQL aggregations have limitations to prepare data sets because they return one column per aggregated group. In general, a significant manual effort is required to build data sets, where a horizontal layout is required. We propose simple, yet powerful, methods to generate SQL code to return aggregated columns in a horizontal tabular layout, returning a set of numbers instead of one number per row. This new class of functions is called horizontal aggregations. Horizontal aggregations build data sets with a horizontal renormalized layout (e.g., point-dimension, observation variable, instance-feature), which is the standard layout required by most data mining algorithms. We propose three fundamental methods to evaluate horizontal aggregations: CASE: Exploiting the programming CASE construct; SPJ: Based on standard relational algebra operators (SPJ queries); PIVOT: Using the PIVOT operator, which is offered by some DBMSs. Experiments with large tables compare the proposed query evaluation methods. Our CASE method has similar speed to the PIVOT operator and it is much faster than the SPJ method. In general, the CASE and PIVOT methods exhibit linear scalability, whereas the SPJ method does not.

IEEE 2012: New Visual Steganography Scheme for Secure Banking Application

IEEE 2012 INTERNATIONAL CONFERENCE ON COMPUTING, ELECTRONICS AND ELECTRICAL TECHNOLOGIES

Abstract— Core banking is a set of services provided by a group of networked bank branches. Bank customers may access their funds and perform other simple transactions from any of the member branch offices. The major issue in core banking is the authenticity of the customer. Due to unavoidable hacking of the databases on the internet, it is always quite difficult to trust the information on the internet. To solve this problem of authentication, we are proposing an algorithm based on image processing, improved Steganography and visual cryptography. This paper proposes technique of encode the password of a customer by improved Steganography, most of the Steganography techniques use either three or four adjacent pixels around a target pixel whereas the proposed technique is able to utilize at most all eight adjacent neighbors so that imperceptibility value grows bigger. and then dividing it into shares. Total number of shares to be created is depending on the scheme chosen by the bank. When two shares are created, one is stored in the Bank database and the others kept by the customer. The customer has to present the share during all of his transactions. This share is stacked with the first share to get the original image. Then decoding method issued to take the hidden password on acceptance or rejection of the output and authenticate the customer

IEEE 2012: Face Recognition using Sparse Approximated Nearest Points between Image Sets

IEEE TRANSACTION ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Abstract— We propose an efficient and robust solution for image set classification. A joint representation of an image set is proposed which includes the image samples of the set and their affine hull model. The model accounts for unseen appearances in the form of affine combinations of sample images. To calculate the between-set distance, we introduce the Sparse Approximated Nearest Point (SANP). SANPs are the nearest points of two image sets such that each point can be sparsely approximated by the image samples of its respective set. This novel sparse formulation enforces sparsity on the sample coefficients and jointly optimizes the nearest points as well as their sparse approximations. Unlike standard sparse coding, the data to be sparsely approximated is not fixed. A convex formulation is proposed to find the optimal SANPs between two sets and the accelerated proximal gradient method is adapted to efficiently solve this optimization. We also derive the kernel extension of the SANP and propose an algorithm for dynamically tuning the RBF kernel parameter while matching each pair of image sets. Comprehensive experiments on the UCSD/Honda, CMU MoBo and YouTube Celebrities face datasets show that our method consistently outperforms the state-of-the-art.

IEEE 2012: Learn to Personalized Image Search from the Photo Sharing Websites

2012 IEEE TRANSACTIONS ON MULTIMEDIA

Abstract— Increasingly developed social sharing websites, like Flicker and YouTube, allow users to create, share, annotate and comment medias. The large-scale user-generated meta-data not only facilitate users in sharing and organizing multimedia content, but provide useful information to improve media retrieval and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework simultaneously considering the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too sparse for topic modeling, we need to enrich users’ annotation pool before user-specific topic spaces construction. The proposed framework contains two components: 1) A Ranking based Multi-correlation Tensor Factorization model is proposed to perform annotation prediction, which is considered as users’ potential annotations for the images; 2) We introduce

User-specific Topic Modeling to map the query relevance and user preference into the same user-specific topic space. For performance evaluation, two resources involved with users’ social Activities are employed. Experiments on a large-scale Flicker dataset demonstrate the effectiveness of the proposed method.

IEEE 2012: Expandable and Cost-Effective Network Structures for Data Centers Using Dual-Port Servers

IEEE 2012 TRANSACTIONS ON COMPUTERS

Abstract— A fundamental goal of data-center networking is to efficiently interconnect a large number of servers with the low equipment cost. Several server-centric network structures for data centers have been proposed. They, however, are not truly expandable and suffer a low degree of regularity and symmetry. Inspired by the commodity servers in today’s data centers that come with dual-port, we consider how to build expandable and cost-effective structures without expensive high-end switches and additional hardware on servers except the two NIC ports. In this paper, two such network structures, called HCN and BCN, are designed, both of which are of server degree 2. We also develop the low-overhead and robust routing mechanisms for HCN and BCN. Although the server degree is only 2, HCN can be expanded very easily to encompass hundreds of thousands servers with the low diameter and high bisection width. Additionally, HCN offers a high degree of regularity, scalability and symmetry, which conform to the modular designs of data centers. BCN is the largest known network structure for data centers with the server degree 2 and network diameter 7. Furthermore, BCN has many attractive features, including the low diameter, high bisection width, large number of node-disjoint paths for the one to- one traffic, and good fault-tolerant ability. Mathematical analysis and comprehensive simulations show that HCN and BCN possess excellent topological properties and are viable network structures for data centers

IEEE 2012: A Novel Anti Phishing framework based on Visual Cryptography

Abstract— With the advent of internet, various online attacks has been increased and among them the most popular attack is phishing. Phishing is an attempt by an individual or a group to get personal confidential information such as passwords, credit card information from unsuspecting victims for identity theft, financial gain and other fraudulent activities. Fake websites which appear very similar to the original ones are being hosted to achieve this. In this paper we have proposed a new approach named as "A Novel Anti-phishing framework based on visual cryptography "to solve the problem of phishing. Here an image based authentication using Visual Cryptography is implemented. The use of visual cryptography is explored to preserve the privacy of an image captcha by decomposing the original image captcha into two shares (known as sheets) that are stored in separate database servers(one with user and one with server) such that the original image captcha can be revealed only when both are simultaneously available; the individual sheet images do not reveal the identity of the original image captcha. Once the original image captcha is revealed to the user it can be used as the password. Using this website cross verifies its identity and proves that it is a genuine website before the end users.

IEEE 2012: Automatic Reconfiguration for Large-Scale Reliable Storage Systems

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING APRIL 2012

Abstract—Byzantine-fault-tolerant replication enhances the availability and reliability of Internet services that store critical state and preserve it despite attacks or software errors. However, existing Byzantine-fault-tolerant storage systems either assume a static set of replicas, or have limitations in how they handle reconfigurations (e.g., in terms of the scalability of the solutions or the consistency levels they provide). This can be problematic in long-lived, large-scale systems where system membership is likely to change during the system lifetime. In this paper, we present a complete solution for dynamically changing system membership in a large-scale Byzantine-fault-tolerant system. We present a service that tracks system membership and periodically notifies other system nodes of membership changes. The membership service runs mostly automatically, to avoid human configuration errors; is itself Byzantine fault-tolerant and reconfigurable; and provides applications with a sequence of consistent views of the system membership. We demonstrate the utility of this membership service by using it in a novel distributed hash table called dBQS that provides atomic semantics even across changes in replica sets. dBQS is interesting in its own right because its storage algorithms extend existing Byzantine quorum protocols to handle changes in the replica set, and because it differs from previous DHTs by providing Byzantine fault tolerance and offering strong semantics. We implemented the membership service and dBQS. Our results show that the approach works well, in practice: the membership service is able to manage a large system and the cost to change the system membership islow.

IEEE 2012: A Flexible Approach to Multisession Trust Negotiations

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING-FEBRUARY 2012

Abstract—Trust Negotiation has shown to be a successful, policy-driven approach for automated trust establishment, through there lease of digital credentials. Current real applications require new flexible approaches to trust negotiations, especially in light of the widespread use of mobile devices. In this paper, we present a multisession dependable approach to trust negotiations. The proposed framework supports voluntary and unpredicted interruptions, enabling the negotiating parties to complete the negotiation despite temporary unavailability of resources. Our protocols address issues related to validity, temporary loss of data, and extended unavailability of one of the two negotiators. A peer is able to suspend an ongoing negotiation and resume it with another (authenticated) peer. Negotiation portions and intermediate states can be safely and privately passed among peers, to guarantee the stability needed to continue suspended negotiations. We present a detailed analysis showing that our protocols have several key properties, including validity, correctness, and minimality. Also, we show how our negotiation protocol can withstand the most significant attacks. As by our complexity analysis, the introduction of the suspension and recovery procedures and mobile negotiations does not significantly increase the complexity of ordinary negotiations. Our protocols require a constant number of messages whose size linearly depend on the portion of trust negotiation that has been carried before the suspensions.

IEEE 2012: A Flexible Approach to Improving System Reliability with Virtual Lockstep

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, FEBRUARY 2012

Abstract— There is an increasing need for fault tolerance capabilities in logic devices brought about by the scaling of transistors to ever smaller geometries. This paper presents a hypervisor-based replication approach that can be applied to commodity hardware to allow for virtually lock stepped execution. It offers many of the benefits of hardware-based lockstep while being cheaper and easier to implement and more flexible in the configurations supported. A novel form of processor state fingerprinting is also presented, which can significantly reduce the fault detection latency. This further improves reliability by triggering rollback recovery before errors are recorded to a checkpoint. The mechanisms are validated using a full prototype and the benchmarks considered indicate an average performance overhead of approximately 14 percent with the possibility for significant optimization. Finally, a unique method of using virtual lockstep for fault injection testing is presented and used to show that significant detection latency reduction is achievable by comparing only a small amount of data across replicas.

IEEE 2012: Design and Implementation of TARF: A Trust-Aware Routing Framework for WSNs

IEEE 2012 Transactions on Dependable and Secure Computing

Abstract— The multi-hop routing in wireless sensor networks (WSNs) offers little protection against identity deception through replaying routing information. An adversary can exploit this defect to launch various harmful or even devastating attacks against the routing protocols, including sinkhole attacks, wormhole attacks and Sybil attacks. The situation is further aggravated by mobile and harsh network conditions. Traditional cryptographic techniques or efforts at developing trust-aware routing protocols do not effectively address this severe problem. To secure the WSNs against adversaries misdirecting the multi-hop routing, we have designed and implemented TARF, a robust trust-aware routing framework for dynamic WSNs. Without tight time synchronization or known geographic information, TARF provides trustworthy and energy-efficient route. Most importantly, TARF proves effective against those harmful attacks developed out of identity deception; the resilience of TARF is verified through extensive evaluation with both simulation and empirical experiments on large-scale WSNs under various scenarios including mobile and RF-shielding network conditions. Further, we have implemented a low-overhead TARF module in TinyOS; as demonstrated, this implementation can be incorporated into existing routing protocols with the least effort. Based on TARF, we also demonstrated a proof-of-concept mobile target detection application that functions well against an anti-detection mechanism.

IEEE 2012: Revisiting Defenses against Large-Scale Online Password Guessing Attacks

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, FEBRUARY 2012

Abstract— Brute force and dictionary attacks on password-only remote login services are now widespread and ever increasing. Enabling convenient login for legitimate users while preventing such attacks is a difficult problem. Automated Turing Tests (ATTs) continue to be an effective, easy-to-deploy approach to identify automated malicious login attempts with reasonable cost of inconvenience to users. In this paper, we discuss the inadequacy of existing and proposed login protocols designed to address large scale online dictionary attacks (e.g., from a Botnet of hundreds of thousands of nodes). We propose a new Password Guessing Resistant Protocol (PGRP), derived upon revisiting prior proposals designed to restrict such attacks. While PGRP limits the total number of login attempts from unknown remote hosts to as low as a single attempt per username, legitimate users in most cases (e.g., when attempts are made from known, frequently-used machines) can make several failed login attempts before being challenged with an ATT. We analyze the performance of PGRP with two real-world data sets and find it more promising than existing proposals.

IEEE 2012: An Intelligent Cloud Computing Architecture Supporting e-Governance

IEEE 2012 AUTOMATION & COMPUTING

Abstract— The development of high speed Internet access, Web 2.0 applications and Virtualization techniques have made Cloud computing a leading edge technology. A user in ‘Cloud’ runs web based application over Internet via browser with a look and feel of desktop program. Cloud computing provides dynamically scalable and virtualized resources as a service over the network at a nominal initial investment. Data-center works as backbone in Cloud computing where a large number of servers are networked to host computing & storage needs of the users. The area which needs more attention is Latency Optimization for cloud architecture to work as ubiquitous as expected. Many data intensive applications produce enormous amounts of data which travel on cloud network. As the cloud users grow, cloud architecture should accommodate movement of voluminous data to avoid data congestion in the network. In this paper, an intelligent & energy efficient Cloud computing architecture is proposed based on distributed data-centers to support application and data access from local data-center with minimum latencies. It was found that the proposed architecture is efficient for business ntre premiers, suitable to apply for e-Governance and provides a green eco-friendly environment for Cloud computing.

IEEE 2012: An Improved Reversible Data Hiding in Encrypted Images Using Side Match

IEEE SIGNAL PROCESSING LETTERS, APRIL 2012

Abstract—This letter proposes an improved version of Zhang’s reversible data hiding method in encrypted images. The original work partitions an encrypted image into blocks, and each block carries one bit by flipping three LSBs of a set of pre-defined pixels. The data extraction and image recovery can be achieved by examining the block smoothness. Zhang’s work did not fully exploit the pixels in calculating the smoothness of each block and did not consider the pixel correlations in the border of neighboring blocks. These two issues could reduce the correctness of data extraction. This letter adopts a better scheme for measuring the smoothness of blocks, and uses the side-match scheme to further decrease the error rate of extracted-bits. The experimental results reveal that the proposed method offers better performance over Zhang’s work. For example, when the block size is set to 8 8, the error rate of the Lena image of the proposed method is 0. 34%, this is significantly lower than 1.21% of Zhang’s work

IEEE 2012: Learn to Personalized Image Search from the Photo Sharing Websites

IEEE TRANSACTION ON MULTIMEDIA, 2012

Abstract—Increasingly developed social sharing websites, like Flicker and YouTube, allow users to create, share, annotate and comment Medias. The large-scale user-generated meta-data not only facilitate users in sharing and organizing multimedia content, but provide useful information to improve media retrieval and management. Personalized search serves as one of such examples where the web search experience is improved by generating the returned list according to the modified user search intents. In this paper, we exploit the social annotations and propose a novel framework simultaneously considering the user and query relevance to learn to personalized image search. The basic premise is to embed the user preference and query-related search intent into user-specific topic spaces. Since the users’ original annotation is too sparse for topic modeling, we need to enrich users’ annotation pool before user-specific topic spaces construction. The proposed framework contains two components: 1) A Ranking based Multi-correlation Tensor Factorization model is proposed to perform annotation prediction, which is considered as users’ potential annotations for the images; 2) We introduce User-specific Topic Modeling to map the query relevance and user preference into the same user-specific topic space. For performance evaluation, two resources involved with users’ social activities are employed. Experiments on a large-scale Flicker data set demonstrate the effectiveness of the proposed method.

IEEE 2011: Going Back and Forth: Efficient Multideployment and Multisnapshotting on Clouds

IEEE/ACM CLOUD COMPUTING June 2011

Abstract — Infrastructure as a Service (IaaS) cloud computing has revolutionized the way we think of acquiring resources by introducing a simple change: allowing users to lease computational resources from the cloud provider’s datacenter for a short time by deploying virtual machines (VMs) on these resources. This new model raises new challenges in the design and development of IaaS middleware. One of those challenges is the need to deploy a large number (hundreds or even thousands) of VM instances simultaneously. Once the VM instances are deployed, another challenge is to simultaneously take a snapshot of many images and transfer them to persistent storage to support management tasks, such as suspend-resume and migration. With datacenters growing rapidly and configurations becoming heterogeneous, it is important to enable efficient concurrent deployment and snapshotting that are at the same time hypervisor independent and ensure a maximum compatibility with different configurations. This paper addresses these challenges by proposing a virtual file system specifically optimized for virtual machine image storage. It is based on a lazy transfer scheme coupled with object versioning that handles snapshotting transparently in a hypervisor-independent fashion, ensuring high portability for different configurations. Large-scale experiments on hundreds of nodes demonstrate excellent performance results: speedup for concurrent VM deployments ranges from a factor of 2 up to 25, with a reduction in bandwidth utilization of as much as 90%.

IEEE 2011: Secure and Practical Outsourcing of Linear Programming in Cloud Computing

IEEE TRANSACTIONS ON CLOUD COMPUTING April 10-15, 2011

Abstract — Cloud Computing has great potential of providing robust computational power to the society at reduced cost. It enables customers with limited computational resources to outsource their large computation workloads to the cloud, and economically enjoy the massive computational power, bandwidth, storage, and even appropriate software that can be shared in a pay-per-use manner. Despite the tremendous benefits, security is the primary obstacle that prevents the wide adoption of this promising computing model, especially for customers when their confidential data are consumed and produced during the computation. Treating the cloud as an intrinsically insecure computing platform from the viewpoint of the cloud customers, we must design mechanisms that not only protect sensitive information by enabling computations with encrypted data, but also protect customers from malicious behaviors by enabling the validation of the computation result. Such a mechanism of general secure computation outsourcing was recently shown to be feasible in theory, but to design mechanisms that are practically efficient remains a very challenging problem. Focusing on engineering computing and optimization tasks, this paper investigates secure outsourcing of widely applicable linear programming (LP) computations. In order to achieve practical efficiency, our mechanism design explicitly decomposes the LP computation outsourcing into public LP solvers running on the cloud and private LP parameters owned by the customer. The resulting flexibility allows us to explore appropriate security/ efficiency trade off via higher-level abstraction of LP computations than the general circuit representation. In particular, by formulating private data owned by the customer for LP problem as a set of matrices and vectors, we are able to develop a set of efficient privacy-preserving problem transformation techniques, which allow customers to transform original LP problem into some arbitrary one while protecting sensitive input/output information. To validate the computation result, we further explore the fundamental duality theorem of LP computation and derive the necessary and sufficient conditions that correct result must satisfy. Such result verification mechanism is extremely efficient and incurs close-to-zero additional cost on both cloud server and customers. Extensive security analysis and experiment results show the immediate practicability of our mechanism design.

IEEE 2011: Enabling Data Hiding for Resource Sharing in Cloud Computing Environments Based on DNA Sequences

2011 IEEE World Congress on Services

Abstract — The main target of this paper is to propose an algorithm to implement data hiding in DNA sequences to increase the confidentiality and complexity by using software point of view in cloud computing environments. By utilizing some interesting features of DNA sequences, the implementation of a data hiding is applied in cloud. The algorithm which has been proposed here is based on binary coding and complementary pair rules. Therefore, DNA reference sequence is chosen and a secret data M is hidden into it as well. As result of applying some steps, M´´´ is come out to upload to cloud environments. The process of identifying and extracting the original data M, hidden in DNA reference sequence begins once clients decide to use data. Furthermore, security issues are demonstrated to inspect the complexity of the algorithm.

IEEE 2011: A Business Model for Cloud Computing Based on a Separate Encryption and Decryption Service

IEEE 2011 Information Science and Applications International Conference April 2011

Abstract — Enterprises usually store data in internal storage and install firewalls to protect against intruders to access the data. They also standardize data access procedures to prevent insiders to disclose the information without permission. In cloud computing, the data will be stored in storage provided by service providers. Service providers must have a viable way to protect their clients’ data, especially to prevent the data from disclosure by unauthorized insiders. Storing the data in encrypted form is a common method of information privacy protection. If a cloud system is responsible for both tasks on storage and encryption/decryption of data, the system administrators may simultaneously obtain encrypted data and decryption keys. This allows them to access information without authorization and thus poses a risk to information privacy. This study proposes a business model for cloud computing based on the concept of separating the encryption and decryption service from the storage service. Furthermore, the party responsible for the data storage system must not store data in plaintext, and the party responsible for data encryption and decryption must delete all data upon the computation on encryption or decryption is complete. A CRM (Customer Relationship Management) service is described in this paper as an example to illustrate the proposed business model. The exemplary service utilizes three cloud systems, including an encryption and decryption system, a storage system, and a CRM application system. One service provider operates the encryption and decryption system while other providers operate the storage and application systems, according to the core concept of the proposed business model. This paper further includes suggestions for a multi-party Service-Level Agreement (SLA) suitable for use in the proposed business model.

IEEE 2011: Enabling Public Audit ability and Data Dynamics for Storage Security in Cloud Computing

IEEE 2011 Transaction Parallel and Distributed Systems, IEEE Transactions on May 2011

Abstract — Cloud computing is the long dreamed vision of computing as a utility, where users can remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. By data outsourcing, users can be relieved from the burden of local data storage and maintenance. Thus, enabling public audit ability for cloud data storage security is of critical importance so that users can resort to an external audit party to check the integrity of outsourced data when needed. To securely introduce an effective third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user. Specifically, our contribution in this work can be summarized as the following three aspects:

1) We motivate the public auditing system of data storage security in Cloud Computing and provide a privacy-preserving auditing protocol, i.e., our scheme supports an external auditor to audit user’s outsourced data in the cloud without learning knowledge on the data content.

2) To the best of our knowledge, our scheme is the first to support scalable and efficient public auditing in the Cloud Computing. In particular, our scheme achieves batch auditing where multiple delegated auditing tasks from different users can be performed simultaneously by the TPA.

3) We prove the security and justify the performance of our proposed schemes through concrete experiments and comparisons with the state-of-the-art.

IEEE 2011: A Secured Cost-effective Multi-Cloud Storage in Cloud Computing

IEEE 2011 Conference on Computer Communications April 2011

Abstract — The end of this decade is marked by a paradigm shift of the industrial information technology towards a pay-per-use service business model known as cloud computing. Cloud data storage redefines the security issues targeted on customer’s outsourced data (data that is not stored/retrieved from the costumers own servers). In this work we observed that, from a customer’s point of view, relying upon a solo SP for his outsourced data is not very promising. In addition, providing better privacy as well as ensure data availability, can be achieved by dividing the user’s data block into data pieces and distributing them among the available SPs in such a way that no less than a threshold number of SPs can take part in successful retrieval of the whole data block. In this paper, we propose a secured cost-effective multi-cloud storage (SCMCS) model in cloud computing which holds an economical distribution of data among the available SPs in the market, to provide customers with data availability as well as secure storage. Our results show that, our proposed model provides a better decision for customers according to their available budgets.

IEEE 2011: Ranking Spatial Data by Quality Preferences

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, March 2011

Abstract— A spatial preference query ranks objects based on the qualities of features in their spatial neighborhood. For example, using a real estate agency database of flats for lease, a customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other features (e.g., restaurants, cafes, hospital, market, etc.) within their spatial neighborhood. Such a neighborhood concept can be specified by the user via different functions. It can be an explicit circular region within a given distance from the flat. Another intuitive definition is to consider the whole spatial domain and assign higher weights to the features based on their proximity to the flat. In this paper, we formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Extensively evaluation of our methods on both real and synthetic data reveals that an optimized branch-and-bound solution is efficient and robust with respect to different parameters.

IEEE 2011: K-N Secret Sharing Visual cryptography Scheme For color Image Using Random number

IEEE INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE AND TECHNOLOGY (IJEST)3 MAR 2011

Abstract— Visual Cryptography is a special encryption technique to hide information in images in such a way that it can be decrypted by the human visual system. The benefit of the visual secret sharing scheme is in its decryption process where without any complex cryptographic computation encrypted data is decrypted using Human Visual System (HVS). But the encryption technique needs cryptographic computation to divide the image into a number of parts let n. k-n secret sharing scheme is a special type of Visual Cryptographic technique where at least a group of k shares out of n shares reveals the secret information, less of it will reveal no information. In our paper we have proposed a new k-n secret sharing scheme for color image where encryption (Division) of the image is done using Random Number generator.

IEEE 2011: Embedded Extended Visual Cryptography Schemes

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, JUNE 2011

Abstract— A visual cryptography scheme (VCS) is a kind of secret sharing scheme which allows the encoding of a secret image into shares distributed to participants. The beauty of such a scheme is that a set of qualified participants is able to recover the secret image without any cryptographic knowledge and computation devices. An extended visual cryptography scheme (EVCS) is a kind of VCS which consists of meaningful shares (compared to the random shares of traditional VCS). In this paper, we propose a construction of EVCS which is realized by embedding random shares into meaningful covering shares, and we call it the embedded EVCS. Experimental results compare some of the well-known EVCSs proposed in recent years systematically, and show that the proposed embedded EVCS has competitive visual quality compared with many of the well-known EVCSs in the literature. In addition, it has many specific advantages against these well-known EVCSs, respectively.

IEEE 2011: A User-Oriented Image Retrieval System Basedon Interactive Genetic Algorithm

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, OCTOBER 2011

Abstract—Digital image libraries and other multimedia databases have been dramatically expanded in recent years. In order to effectively and precisely retrieve the desired images from a large image database, the development of a content-based image retrieval (CBIR) system has become an important research issue. However, most of the proposed approaches emphasize on finding the best representation for different image features. Furthermore, very few of the representative works well consider the user’s subjectivity and preferences in the retrieval process. In this paper, a user-oriented mechanism for CBIR method based on an interactive genetic algorithm (IGA) is proposed. Color attributes like the mean value, the standard deviation, and the image bitmap of a color image are used as the features for retrieval. In addition, the entropy based on the gray level co-occurrence matrix and the edge histogram of an image is also considered as the texture features. Furthermore, to reduce the gap between the retrieval results and the users’ expectation, the IGA is employed to help the users identify the images that are most satisfied to the users’ need. Experimental results and comparisons demonstrate the feasibility of the proposed approach

IEEE 2011: Sketch4Match – Content-based Image Retrieval System Using Sketches

IEEE INTERNATIONAL SYMPOSIUM ON APPLIED MACHINE INTELLIGENCE AND INFORMATICS • JANUARY, 2011

Abstract— The content based image retrieval (CBIR) is one of the most popular, rising research areas of the digital image processing. Most of the available image search tools, such as Google Images and Yahoo! Image search, are based on textual annotation of images. In these tools, images are manually annotated with keywords and then retrieved using text-based search methods. The performances of these systems are not satisfactory. The goal of CBIR is to extract visual content of an image automatically, like color, texture, or shape. This paper aims to introduce the problems and challenges concerned with the design and the creation of CBIR systems, which is based on a free hand sketch (Sketch based image retrieval – SBIR). With the help of the existing methods, describe a possible solution how to design and implement a task spesi_c descriptor, which can handle the informational gap between a sketch and a colored image, making an opportunity for the efficient search hereby. The used descriptor is constructed after such special sequence of preprocessing steps that the transformed full color image and the sketch can be compared. We have studied EHD, HOG and SIFT. Experimental results on two sample databases showed good results. Overall, the results show that the sketch based system allows users an intuitive access to search-tools. The SBIR technology can be used in several applications such as digital libraries, crime prevention, and photo sharing sites. Such system has great value in apprehending suspects and indentifying victims in forensics and law enforcement. A possible application is matching a forensic sketch to a gallery of mug shot images. The area of retrieve images based on the visual content of the query picture intensi_ed recently, which demands on the quite wide methodology spectrum on the area of the image processing

IEEE 2011: Nymble: Blocking Misbehaving Users in Anonymizing Networks

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, MARCH-APRIL 2011

Abstract— Anonymizing networks such as Tor allow users to access Internet services privately by using a series of routers to hide the client’s IP address from the server. The success of such networks, however, has been limited by users employing this anonymity for abusive purposes such as defacing popular Web sites. Web site administrators routinely rely on IP-address blocking for disabling access to misbehaving users, but blocking IP addresses is not practical if the abuser routes through an Anonymizing network. As a result, administrators block all known exit nodes of Anonymizing networks, denying anonymous access to misbehaving and behaving Users alike. To address this problem, we present Nymble, a system in which servers can “blacklist” misbehaving users, thereby blocking users without compromising their anonymity. Our system is thus agnostic to different servers’ definitions of misbehavior—servers can blacklist users for whatever reason, and the privacy of blacklisted users is maintained.

IEEE 2011: SAT: A Security Architecture Achieving Anonymity and Traceability in Wireless Mesh Networks

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, MARCH-APRIL 2011

Abstract— Anonymity has received increasing attention in the literature due to the users’ awareness of their privacy nowadays. Anonymity provides protection for users to enjoy network services without being traced. While anonymity-related issues have been extensively studied in payment-based systems such as e-cash and peer-to-peer (P2P) systems, little effort has been devoted to wireless mesh networks (WMNs). On the other hand, the network authority requires conditional anonymity such that misbehaving entities in the network remain traceable. In this paper, we propose a security architecture to ensure unconditional anonymity for honest users and traceability of misbehaving users for network authorities in WMNs. The proposed architecture strives to resolve the conflicts between the anonymity and traceability objectives, in addition to guaranteeing fundamental security requirements including authentication, confidentiality, data integrity, and no repudiation. Thorough analysis on security and efficiency is incorporated, demonstrating the feasibility and effectiveness of the proposed architecture

IEEE 2011: Modeling and Detection of Camouflaging Worm

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING , MAY-JUNE 2011

Abstract— Active worms pose major security threats to the Internet. This is due to the ability of active worms to propagate in an automated fashion as they continuously compromise computers on the Internet. Active worms evolve during their propagation and thus pose great challenges to defend against them. In this paper, we investigate a new class of active worms, referred to as Camouflaging Worm (C-Worm in short). The C-Worm is different from traditional worms because of its ability to intelligently manipulate its scan traffic volume over time. Thereby, the C-Worm camouflages its propagation from existing worm detection systems based on analyzing the propagation traffic generated by worms. We analyze characteristics of the C-Worm and conduct a comprehensive comparison between its traffic and non-worm traffic (background traffic). We observe that these two types of traffic are barely distinguishable in the time domain. However, their distinction is clear in the frequency domain, due to the recurring manipulative nature of the C-Worm. Motivated by our observations, we design a novel spectrum-based scheme to detect the C-Worm. Our scheme uses the Power Spectral Density (PSD) distribution of the scan traffic volume and its corresponding Spectral Flatness Measure (SFM) to distinguish the C-Worm traffic from background traffic. Using a comprehensive set of detection metrics and real-world traces as background traffic, we conduct extensive performance evaluations on our proposed spectrum-based detection scheme. The performance data clearly demonstrates that our scheme can effectively detect the C-Worm propagation. Furthermore, we show the generality of our spectrum-based scheme in effectively detecting not only the C-Worm, but traditional worms as well.

IEEE 2011: A New Approach for FEC Decoding Based on the BP Algorithm in LTE and WiMAX Systems

IEEE Conference on Information Theory; May 2011

Abstract— Many wireless communication systems such as IS- 54, enhanced data rates for the GSM evolution (EDGE), worldwide interoperability for microwave access (WiMAX) and long term evolution (LTE) have adopted low-density parity-check (LDPC), tail-biting convolution, and turbo codes as the forward error correcting codes (FEC) scheme for data and overhead channels. Therefore, many efficient algorithms have been proposed for decoding these codes. However, the different decoding approaches for these two families of codes usually lead to different hardware architectures. Since these codes work side by side in these new wireless systems, it is a good idea to introduce a universal decoder to handle these two families of codes. The present work exploits the parity-check matrix (H) representation of tail biting convolution and turbo codes, thus enabling decoding via a unified belief propagation (BP) algorithm. Indeed, the BP algorithm provides a highly effective general methodology for devising low-complexity iterative decoding algorithms for all convolution code classes as well as turbo codes. While a small performance loss is observed when decoding turbo codes with BP instead of MAP, this is offset by the lower complexity of the BP algorithm and the inherent advantage of a unified decoding Architecture

IEEE 2011: Intrusion detection: An Energy efficient approach in Heterogeneous WSN

IEEE PROCEEDINGS OF ICETECT 2011

Abstract— Intrusion detection plays an important role in the area of security in WSN. Detection of any type of intruder is essential in case of WSN. WSN consumes a lot of energy to detect an intruder. Therefore we derive an algorithm for energy efficient external and internal intrusion detection. We also analyse the probability of detecting the intruder for heterogeneous WSN. This paper considers single sensing and multi sensing intruder detection models. It is found that our experimental results validate the theoretical results.

IEEE 2011: Network Coding Based Privacy Preservation against Traffic Analysis in Multi-Hop Wireless Networks

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, MARCH 2011

Abstract— Privacy threat is one of the critical issues in multihop wireless networks, where attacks such as traffic analysis and flow tracing can be easily launched by a malicious adversary due to the open wireless medium. Network coding has the potential to thwart these attacks since the coding/mixing operation is encouraged at intermediate nodes. However, the simple deployment of network coding cannot achieve the goal once enough packets are collected by the adversaries. On the other hand, the coding/mixing nature precludes the feasibility of employing the existing privacy-preserving techniques, such as Onion Routing. In this paper, we propose a novel network coding based privacy-preserving scheme against traffic analysis in multihop wireless networks. With homomorphism encryption on Global Encoding Vectors (GEVs), the proposed scheme offers two significant privacy-preserving features, packet flow intractability and message content confidentiality, for efficiently thwarting the traffic analysis attacks. Moreover, the proposed scheme keeps the random coding feature, and each sink can recover the source packets by inverting the GEVs with a very high probability. Theoretical analysis and simulative evaluation demonstrate the validity and efficiency of the proposed scheme

IEEE 2011: Scalable and Cost-Effective Interconnection of Data-Center Servers Using Dual Server Ports

IEEE/ACM TRANSACTIONS ON NETWORKING

Abstract— The goal of data-center networking is to interconnect a large number of server machines with low equipment cost while providing high network capacity and high bisection width. It is well understood that the current practice where servers are connected by a tree hierarchy of network switches cannot meet these requirements. In this paper, we explore a new server-interconnection structure. We observe that the commodity server machines used in today’s data centers usually come with two built-in Ethernet ports, one for network connection and the other left for backup purposes. We believe that if both ports are actively used in network connections, we can build a scalable, cost-effective interconnection structure without either the expensive higher-level large switches or any additional hardware on servers. We design such a networking structure called FiConn. Although the server node degree is only 2 in this structure, we have proven that FiConn is highly scalable to encompass hundreds of thousands of servers with low diameter and high bisection width. We have developed a low-overhead traffic-aware routing mechanism to improve effective link utilization based on dynamic traffic state. We havealso proposed how to incrementally deploy FiConn.

IEEE 2011: Improving the Performance of Wireless Ad Hoc Networks through MAC Layer Design

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, JANUARY 2011

Abstract— In this paper, the performance of the ALOHA and CSMA MAC protocols are analyzed in spatially distributed wireless networks. The main system objective is correct reception of packets, and thus the analysis is performed in terms of outage probability. In our network model, packets belonging to specific transmitters arrive randomly in space and time according to a 3-D Poisson point process, and are then transmitted to their intended destinations using a fully-distributed MAC protocol. A packet transmission is considered successful if the received SINR is above a predefined threshold for the duration of the packet. Accurate bounds on the outage probabilities are derived as a function of the transmitter density, the number of back offs and retransmissions, and in the case of CSMA, also the sensing threshold. The analytical expressions are validated with simulation results. For continuous-time transmissions, CSMA with receiver sensing (which involves adding a feedback channel to the conventional CSMA protocol) is shown to yield the best performance. Moreover, the sensing threshold of CSMA is optimized. It is shown that introducing sensing for lower densities (i.e., in sparse networks) is not beneficial, while for higher densities (i.e., in dense networks), using an optimized sensing threshold provides significant gain.

IEEE 2011: A Privacy-Preserving Location Monitoring System for Wireless Sensor Networks

IEEE TRANSACTIONS ON MOBILE COMPUTING, Jan 2011

Abstract— Monitoring personal locations with a potentially entrusted server poses privacy threats to the monitored individuals. To this end, we propose a privacy-preserving location monitoring system for wireless sensor networks. In our system, we design two in network location anonymization algorithms, namely, resource- and quality-aware algorithms that aim to enable the system to provide high quality location monitoring services for system users, while preserving personal location privacy. Both algorithms rely on the well established k-anonymity privacy concept, that is, a person is indistinguishable among k persons, to enable trusted sensor nodes to provide the aggregate location information of monitored persons for our system. Each aggregate location is in a form of a monitored area A along with the number of monitored persons residing in A, where A contains at least k persons. The resource-aware algorithm aims to minimize communication and computational cost, while the quality-aware algorithm aims to maximize the accuracy of the aggregate locations by minimizing their monitored areas. To utilize the aggregate location information to provide location monitoring services, we use a spatial histogram approach that estimates the distribution of the monitored persons based on the gathered aggregate location information. Then the estimated distribution is used to provide location monitoring services through answering range queries. We evaluate our system through simulated experiments. The results show that our system provides high quality location monitoring services for system users and guarantees the location privacy of the monitored persons

IEEE 2011: ROC: Resilient Online Coverage for Surveillance Applications

IEEE/ACM TRANSACTIONS ON NETWORKING, FEBRUARY 2011

Abstract— We consider surveillance applications in which sensors are deployed in large numbers to improve coverage fidelity. Previous research has studied how to select active sensor covers (subsets of nodes that cover the field) to efficiently exploit redundant node deployment and tolerate unexpected node failures. Little attention was given to studying the tradeoff between fault tolerance and energy efficiency in sensor coverage. In this work, our objectives are twofold. First, we aim at rapidly restoring field coverage under unexpected sensor failures in an energy-efficient manner. Second, we want to flexibly support different degrees of redundancy in the field without needing centralized control. To meet these objectives, we propose design guidelines for applications that employ distributed cover-selection algorithms to control the degree of redundancy at local regions in the field. In addition, we develop a new distributed technique to facilitate switching between active covers without the need for node synchronization. Distributed cover selection protocols can be integrated into our referred to as “resilient online coverage” (ROC) framework. A key novelty in ROC is that it allows every sensor to control the degree of redundancy and surveillance in its region according to current network conditions. We analyze the benefits of ROC in terms of energy efficiency and fault tolerance. Through extensive simulations, we demonstrate the effectiveness of ROC in operational scenarios and compare its performance with previous surveillance techniques.

IEEE 2011: Caching Strategies Based on Information Density Estimation in Wireless Ad Hoc Networks

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, JUNE 2011

Abstract— We address cooperative caching in wireless networks, where the nodes may be mobile and exchange information in a peer-to-peer fashion. We consider both cases of nodes with large and small-sized caches. For large-sized caches, we devise a strategy where nodes, independent of each other, decide whether to cache some content and for how long. In the case of small-sized caches, we aim to design a content replacement strategy that allows nodes to successfully store newly received information while maintaining the good performance of the content distribution system. Under both conditions, each node takes decisions according to its perception of what nearby users may store in their caches and with the aim of differentiating its own cache content from the other nodes’. The result is the creation of content diversity within the nodes neighborhood so that a requesting user likely finds the desired information nearby. We simulate our caching algorithms indifferent ad hoc network scenarios and compare them with other caching schemes, showing that our solution succeeds in creating the desired content diversity, thus leading to a resource-efficient information access.

IEEE 2010: PAM: An Efficient and Privacy-Aware Monitoring Framework for Continuously Moving Objects

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, MARCH 2010

Abstract— Efficiency and privacy are two fundamental issues in moving object monitoring. This paper proposes a privacy-aware monitoring (PAM) framework that addresses both issues. The framework distinguishes itself from the existing work by being the first to holistically address the issues of location updating in terms of monitoring accuracy, efficiency, and privacy, particularly, when and how mobile clients should send location updates to the server. Based on the notions of safe region and most probable result, PAM performs location updates only when they would likely alter the query results. Furthermore, by designing various client update strategies, the framework is flexible and able to optimize accuracy, privacy, or efficiency. We develop efficient query evaluation/reevaluation and safe region computation algorithms in the framework. The experimental results show that PAM substantially outperforms traditional schemes in terms of monitoring accuracy, CPU cost, and scalability while achieving close-to-optimal communication cost.

IEEE 2010: Layered Approach Using Conditional Random Fields for Intrusion Detection

IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, MARCH 2010

Abstract— Intrusion detection faces a number of challenges; an intrusion detection system must reliably detect malicious activities in a network and must perform efficiently to cope with the large amount of network traffic. In this paper, we address these two issues of Accuracy and Efficiency using Conditional Random Fields and Layered Approach. We demonstrate that high attack detection accuracy can be achieved by using Conditional Random Fields and high efficiency by implementing the Layered Approach. Experimental results on the benchmark KDD ’99 intrusion data set show that our proposed system based on Layered Conditional Random Fields outperforms other well-known methods such as the decision trees and the naïve Bayes. The improvement in attack detection accuracy is very high, particularly, for the U2R attacks (34.8 percent improvement) and the R2L attacks (34.5 percent improvement). Statistical Tests also demonstrate higher confidence in detection accuracy for our method. Finally, we show that our system is robust and is able to handle noisy data without compromising performance.

IEEE 2010: A Scheduling and Call Admission Control Algorithm for WiMax Mesh Network with Strict QoS Guarantee

IEEECOMMUNICATION SYSTEMS AND NETWORKS (COMSNETS), 2010

Abstract— The IEEE 802.16 standard (commonly known as WiMax) has emerged as a broadband wireless technology covering large geographical area while providing high speed data rates with native Quality of Service (QoS) support. In this paper, we study mesh mode of operation of WiMax with centralized scheduling for UGS and RTPS service classes. We briefly discuss two known routing algorithms (to find the path of a request) and propose two new routing algorithms. We present a novel scheduling and Call Admission Control (CAC) algorithm for UGS and RTPS service class. The scheduling and CAC algorithm make sure that each and every packet of admitted request strictly meets its delay and jitter constraints. Since an RTPS request can change its data rate requirement, we propose an efficient algorithm for computing extra bandwidth request for RTPS service class which perform much better in terms of average packet delay and packet drop percentage compared to some simple algorithms. We present simulation results comparing our scheduling algorithm with two other algorithms proposed in the literature. We also present results which show that our scheduling does provide strict QoS guarantee for every packet.

IEEE 2008: Image Segmentation by Resonance Algorithm

IEEE SICE ANNUAL CONFERENCE, 2008

Abstract— Computer vision and recognition plays more important role on intelligent control. In this paper, the image segmentation is done by the resonance theory. Resonance algorithm is an unsupervised method to generate the region (feature space) from similar pixels (feature vectors) in an image. It tolerates gradual changes of texture to some extent for image segmentation. The purpose of the paper is to propose a practical method for image segmentation, which is always the first step to control a real intelligent control system.

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