WATERMARKING RELATIONAL DATABASES USING OPTIMIZATION BASED TECHNIQUES

Abstract

Proving ownership rights on outsourced relational databases is a crucial issue in today‘s internet-based application environments and in many content distribution applications. In this dissertation, a mechanism is presented for proof of ownership and ownership identification based on the secure embedding of a robust imperceptible watermark in relational data. Watermarking problem of relational databases is formulated as a constrained optimization problem and Genetic and Bacterial Foraging Optimization algorithms are implemented to solve the optimization problem and to handle the constraints. Proposed watermarking technique is resilient to watermark synchronization errors because it uses a partitioning approach that does not require marker tuples. Watermark decoding is based on a threshold-based technique characterized by an optimal threshold that minimizes the probability of decoding errors. Experimental results have shown that technique proposed in this dissertation is resilient to tuple deletion, alteration, and insertion attacks.