Design and Analysis of an Intelligent Integrity Checking Watermarking Scheme for Ubiquitous Database Access

International Journal of artificial intelligence research

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Field Value
 
Title Design and Analysis of an Intelligent Integrity Checking Watermarking Scheme for Ubiquitous Database Access
 
Creator Darwish, Saad Mohamed
Selim, Hosam A.
 
Subject Artificial Intelligence
Ubiquitous database accessing, Distortion free watermarking, Genetic algorithm, intelligent Content Integrity mechanism
 
Description As a result of the highly distributed nature of ubiquitous database accessing, it is essential to develop security mechanisms that lend themselves well to the delicate properties of outsourcing databases integrity and copyright protection. Researchers have begun to study how watermarking computing can make ubiquitous databases accessing more confident work environments. One area where database context may help is in supporting content integrity. Initially, most of the research effort in this field was depending on distortion based watermark while the few remaining studies concentrated on distortion-free. But there are many disadvantages in previous studies; most notably some rely on adding watermark as an extra attributes or tuples, which increase the size of the database. Other techniques such as permutation and abstract interpretation framework require much effort to verify the watermark. The idea of this research is to adapt an optimized distortion free watermarking based on fake tuples that are embedded into a separate file not within the database to validate the content integrity for ubiquitous database accessing. The proposed system utilizes the GA, which boils down its role to create the values of the fake tuples as watermark to be the closest to real values. So that it's very hard to any attacker to guess the watermark. The proposed technique achieves more imperceptibility and security. Experimental outcomes confirm that the proposed algorithm is feasible, effective and robust against a large number of attacks.
 
Publisher STMIK Dharma Wacana
 
Contributor Alexandria University, Egypt
 
Date 2018-12-07
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Identifier http://ijair.id/index.php/ijair/article/view/65
10.29099/ijair.v3i1.65
 
Source International Journal of Artificial Intelligence Research; Vol 3, No 1 (2019): In Pres
2579-7298
10.29099/ijair.v3i1
 
Language en
 
Relation http://ijair.id/index.php/ijair/article/downloadSuppFile/65/17
 
Rights Copyright (c) 2018 International Journal of Artificial Intelligence Research
https://creativecommons.org/licenses/by-sa/4.0
 

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