文章基本信息

标题：A Survey on Applying Metric Preserving Transformation of Robust Watermarking for Relational Database
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作者：T. Jaison Vimalraj ; S. Praveena ; S. Vishnupriya 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：3
页码：4376
DOI：10.15680/IJIRCCE.2016.0403216
出版社：S&S Publications
摘要：In this paper, we show another powerful database fragile watermarking scheme, the innovation of which stands on a semantic control of the information bending and on the expansion of quantization Index Modulation (QIM) to round histograms of numerical qualities. With the arrival of Index based Hashing technique, it is easier to retrieve data. Thereafter prioritize it by Metric Preserving Transformation. The semantic contortion control of the installing process we propose depends on the ID of e xisting semantic connections in the middle of estimations of properties in a tuple by method for a meta - physics. Thusly, we maintain a strategic distance from indistinguishable or extremely uncommon record events which might inclination information transla tion on the other hand sell out the vicinity of the watermark. In a brief moment time, we adjust QIM to database watermarking. Watermark implanting is directed by adjusting the relative rakish position of the round histogram focal point of mass of one nume rical characteristic. We hypothetically exhibit the power execution of our plan against most regular assaults (i.e., tuple insertion and erasure). This makes it suitable for copyright insurance, proprietor recognizable proof, or deceiver following purposes . We promote check tentatively these hypothetical points of confinement inside of the system of candidate passport details. Under the supposition forced by the focal cut off hypothesis, exploratory results fit the hypothesis. We too contrast our methodolog y and two proficient plans to de monstrate its advantages
关键词：RobustWatermarking; QIM; Index based hashing; Metric preserving Transformation