A reversible database watermarking method non-redundancy shifting-based histogram gaps. (May 2020)

• Record Type: Journal Article
• Authors: Li, Yan; Wang, Junwei; Luo, Xiangyang
• Is Part Of: International journal of distributed sensor networks. Volume 16:Number 5(2020)
• Publication Date: 2020-05
• Subjects: Reversible database watermark -- data distortion -- histogram gap -- low distortion -- non-redundancy shifting; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147720921769
• Languages: English
• ISSNs: 1550-1329

Abstract

In relational databases, embedding watermarks in integer data using traditional histogram shifting method has the problem of large data distortion. To solve this problem, a reversible database watermarking method without redundant shifting distortion is proposed, taking advantage of a large number of gaps in the integer histogram. This method embeds the watermark bit by bit on the basis of grouping. First, an integer data histogram is constructed with the absolute value of the prediction error of the data as a variable. Second, the positional relationship between each column and the gap in the histogram is analyzed to find out all the columns adjacent to the gap. Third, the highest column is selected as the embedded point. Finally, a watermark bit is embedded on the group by the histogram non-redundant shifting method. Experimental results show that compared with existing reversible database watermarking methods, such as genetic algorithm and histogram shift watermarking and histogram gap–based watermarking, the proposed method has no data distortion caused by the shifting redundant histogram columns after embedding watermarks on forest cover type data set and effectively reduces the data distortion rate after embedding watermarks.