Wednesday, 15 July 2015

IEEE 2015 : Privacy-Preserving Detection of Sensitive Data Exposure

IEEE 2015 IEEE 2015 Transaction on Data Mining

Abstract : Statistics from security firms, research institutions and government organizations show that the number of data-leak instances have grown rapidly in recent years. Among various data-leak cases, human mistakes are one of the main causes of data loss. There exist solutions detecting inadvertent sensitive data leaks caused by human mistakes and to provide alerts for organizations. A common approach is to screen content in storage and transmission for exposed sensitive information. Such an approach usually requires the detection operation to be conducted in secrecy. However, this secrecy requirement is challenging to satisfy in practice, as detection servers may be compromised or outsourced. In this paper, we present a privacypreserving data-leak detection (DLD) solution to solve the issue where a special set of sensitive data digests is used in detection. The advantage of our method is that it enables the data owner to safely delegate the detection operation to a semihonest provider without revealing the sensitive data to the provider. We describe how Internet service providers can offer their customers DLD as an add-on service with strong privacy guarantees. The evaluation results show that our method can support accurate detection with very small number of false alarms under various data-leak scenarios.

IEEE 2015 : An Energy-Efficient and Delay-Aware Wireless Computing System for Industrial Wireless Sensor Networks

IEEE 2015 Transactions on Parallel and Distributed Systems  

Abstract :Industrial wireless sensor networks have attracted much attention as a cornerstone to making the smart factories real. Utilizing industrial wireless sensor networks as a base for smart factories makes it possible to optimize the production line without human resources since it provides industrial Internet of Things (IoT) service, where various types of data are collected from sensors and mined to control the machines based on the analysis result. On the other hand, a fog computing node, which executes such real-time feedback control, should be capable of real-time data collection, management, and processing. To achieve these requirements, in this paper, we introduce Wireless Computing System (WCS) as a fog computing node. Since there are a lot of servers and each server has 60 GHz antennas to connect to other servers and sensors, WCS has high collecting and processing capabilities. However, in order to fulfill a demand for real-time feedback control, WCS needs to satisfy an acceptable delay for data collection. Additionally, lower power consumption is required in order to reduce the cost for factory operation. Therefore, we propose an Energy-Efficient and Delay-Aware Wireless Computing System (E2DA-WCS). Since there is a tradeoff relationship between the power consumption and the delay for data collection, our proposed system controls the sleep schedule and the number of links to minimize the power consumption while satisfying an acceptable delay constraint. Furthermore, the effectiveness of our proposed system is evaluated through extensive computer simulations.