Abstract
Because of the increasingly dispersed existence of universal access to databases, it is important to establish security measures that allow the delicate properties of privacy and copyright rights of outsourcing databases. Researchers started studying how watermarking software would allow pervasive datasets accessing more secure work environments. Initially, most analyses in this area relied on distortion-based watermark, whilst the few remaining studies centered on distortion-free. But there are also drawbacks in previous studies; most importantly some depend on inserting watermark as additional attributes or tuples, raising the sample capacity. Other approaches like permutation and abstract representation system need significant effort to validate the watermark. The aim of this research is to implement an advanced distortion-free watermarking focused on fake tuples embedded in a non-domain separate file to verify material quality for pervasive database entry. The proposed scheme uses the GA, which reduces its function to establish the values of false tuples as a watermark nearest to actual values. But an intruder can hardly infer the watermark. The latest technique provides imperceptibility and stability. Experimental findings suggest that the proposed algorithm is feasible, reliable, and resilient against several attacks.
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Ismail, A.A., Darwish, S.M. (2021). Context-Based Zero Database Watermarking Scheme Based on Evolutionary Mechanism. In: Hassanien, AE., Chang, KC., Mincong, T. (eds) Advanced Machine Learning Technologies and Applications. AMLTA 2021. Advances in Intelligent Systems and Computing, vol 1339. Springer, Cham. https://doi.org/10.1007/978-3-030-69717-4_94
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DOI: https://doi.org/10.1007/978-3-030-69717-4_94
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