Abstract
: Advancement in information technology
is playing an increasing role in the use of information systems comprising
relational databases. These databases are used effectively in
collaborative environments for information extraction; consequently, they
are vulnerable to security threats concerning ownership rights and data
tampering. Watermarking is advocated to enforce ownership rights over
shared relational data and for providing a means for tackling data tampering.
When ownership rights are enforced using watermarking, the underlying data
undergoes certain modifications; as a result of which, the data quality gets
compromised. Reversible watermarking is employed to ensure data quality
along-with data recovery. However, such techniques are usually not robust
against malicious attacks and do not provide any mechanism to selectively
watermark a particular attribute by taking into account its role
in knowledge discovery. Therefore, reversible watermarking is required
that ensures; (i) watermark encoding and decoding by accounting for the
role of all the features in knowledge discovery; and, (ii) original data
recovery in the presence of active malicious attacks. In this paper, a
robust and semi-blind reversible watermarking (RRW) technique for numerical
relational data has been proposed that addresses the above objectives.
Experimental studies prove the effectiveness of RRW against malicious attacks
and show that the proposed technique outperforms existing ones.
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