Reversible Watermarking Technique for Relational Data using Ant Colony Optimization and Encryption
Sharafunisa S1, Smitha E S2
1Sharafunisa S, M.Tech Scholar, Department of Computer Science and Engineering, LBS Institute of Technology for Women, Thiruvananthapuram (Kerala), India.
2Smitha E S, Associate Professor, Department of Computer Science and Engineering, LBS Institute of Technology for Women, Thiruvananthapuram (Kerala), India.
Manuscript received on 13 August 2016 | Revised Manuscript received on 20 August 2016 | Manuscript Published on 30 August 2016 | PP: 147-151 | Volume-5 Issue-6, August 2016 | Retrieval Number: F4705085616/16©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Data is stored in different digital formats such as images, audio, video, natural language texts and relational data. Relational data in particular is shared extensively by the owners with communities for research purpose and in virtual storage locations in the cloud. The purpose is to work in a collaborative environment where data is openly available for decision making and knowledge extraction process. So there is a need to protect these data from various threats like ownership claiming, piracy, theft, etc. Watermarking is a solution to overcome these issues. Watermark is considered to be some kind of information that is embedded into the underlying data. While embedding the watermark, the data may modify, to overcome this we use reversible watermarking in which owner can recover the data after watermarking. In this paper, a reversible watermarking for relational data has been proposed that uses ant colony optimization and encryption for more accuracy and security.
Keywords: Ant Colony Optimization (ACO), Mutual Information (MI), Reversible Watermarking, Data Recovery, Genetic Algorithm (GA).
Scope of the Article: Discrete Optimization