Survey on Relational Database Watermarking Employing Evolutionary Methods

Abstract

Ownership control, integrity, and tamper-proofing of relational data are essential concerns that must be addressed as the communication (network) system grows. Over the past several years, a plethora of potential solutions has been proposed to address these issues (including cryptography, steganography, digital signatures, watermarks, and many others). Digital watermarking (comparatively new) is a technology that aids in the resolution of issues such as data theft, authenticity, and copyright claims. This paper’s primary contributions are as follows: 1) Examine evolutionary algorithm-based watermarking in relational databases that provide optimize data encoding space in search space which provides high robustness and imperceptibility. 2) Examine contemporary database watermarking strategies based on evolutionary algorithms for high embedding capacity and watermark bit insertion. 3) Malicious agent tracing through cluster-based (mainly fuzzy c-mean clustering algorithm or based on a hash function) or multiple watermarking approaches over shared or collaborative networks. This article focuses on watermarking numeric relational databases for authentication and integrity. Also provide a brief overview of the development of relational database watermarking and emergence, its characteristics and application, and the popular research methods currently in use. In addition, gist on various possible attacks. At last, this paper suggests directions for further research in these areas. Researchers can use the findings of this study to build secure watermarking methods for databases.