Robust Watermarking of Relational Databases Based on Extension of Quantization Index Modulation to Circular Histograms release_emvepz3lobaprovzbnkyvrarqm

by Miss Priya, G Tale, R Dharaskar, V Thakare

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In the internet and cloud computing paradigms the use of digital data is increasing excessively, where such kind of data is stored in various digital formats and also in related nature as a relational data. Watermarking methods has been proposed for multimedia, digital documents, software and, more recently, for databases. Two categories, depending on application, distinguish watermarks: fragile watermarks for tamper detection and robust watermarks for ownership verification.In this paper, a new robust database watermarking scheme the origin of which is based on a semantic control of the data distortion and on the extension of quantization index modulation (QIM) to circular histograms of numeric and non-numeric attributes is proposed. It can be used for verifying database authentication as well as for traceability when identifying database origin after it has been modified. With feature region selection method, a non-overlapping feature region set is selected which has the greatest robustness against various attacks and can preserve data quality as much as possible after watermarked. This work is formulated by a multidimensional knapsack problem (MDKP) and solved by a genetic algorithm based approach. An experimental result of the proposed scheme indicates improved watermark capacity with less distortion and maintains original data quality.
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