An Efficient Watermarking Technique Using Genetic Algorithm for Relational Data

Abstract

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 the data quality gets compromised. Reversible watermarking is employed to ensure data quality along with data recovery. Reversible watermarking tries to overcome the problem of data quality degradation by allowing recovery of original data along with the embedded watermark information. An optimal watermark value is created through the Genetic Algorithm (GA) and inserted into the selected feature of the relational database. It mainly comprises a data preprocessing phase, watermark encoding phase, attacker channel, watermark decoding phase and data recovery phase. In data preprocessing phase, secret parameters are defined and strategies are used to analyze and rank features to watermark. An optimum watermark string is created in this phase by employing GA an optimization scheme that ensures reversibility without data quality loss.