A 3D Steganalytic Algorithm and Steganalysis-Resistant Watermarking
Ying Yang, Ruggero Pintus, Holly Rushmeier, and Ioannis Ivrissimtzis
February 2017
Abstract
We propose a simple yet efficient steganalytic algorithm for watermarks embedded by two state-of-the-art 3D watermarking algorithms by Cho et al. The main observation is that while in a clean model the means/variances of Cho et al.'s normalized histogram bins are expected to follow a Gaussian distribution, in a marked model their distribution will be bimodal. The proposed algorithm estimates the number of bins through an exhaustive search and then the presence of a watermark is decided by a tailor made normality test or a t-test. We also propose a modification of Cho et al.'s watermarking algorithms with the watermark embedded by changing the histogram of the radial coordinates of the vertices. Rather than targeting a continuous statistics such as the mean or variance of the values in a bin, the proposed watermarking modifies a discrete statistic, which here is the height of the histogram bin, to achieve watermark embedding. Experimental results demonstrate that the modified algorithm offers not only better resistance against the steganalytic attack we developed, but also an improved robustness/capacity trade-off.
Reference and download information
Ying Yang, Ruggero Pintus, Holly Rushmeier, and Ioannis Ivrissimtzis. A 3D Steganalytic Algorithm and Steganalysis-Resistant Watermarking. IEEE Transactions on Visualization and Computer Graphics, 23(2): 1002-1013, February 2017. DOI: 10.1109/TVCG.2016.2525771.
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Bibtex citation record
@Article{Yang:2017:3SA, author = {Ying Yang and Ruggero Pintus and Holly Rushmeier and Ioannis Ivrissimtzis}, title = {A {3D} Steganalytic Algorithm and Steganalysis-Resistant Watermarking}, journal = {IEEE Transactions on Visualization and Computer Graphics}, volume = {23}, number = {2}, pages = {1002--1013}, month = {February}, year = {2017}, abstract = { We propose a simple yet efficient steganalytic algorithm for watermarks embedded by two state-of-the-art 3D watermarking algorithms by Cho et al. The main observation is that while in a clean model the means/variances of Cho et al.'s normalized histogram bins are expected to follow a Gaussian distribution, in a marked model their distribution will be bimodal. The proposed algorithm estimates the number of bins through an exhaustive search and then the presence of a watermark is decided by a tailor made normality test or a t-test. We also propose a modification of Cho et al.'s watermarking algorithms with the watermark embedded by changing the histogram of the radial coordinates of the vertices. Rather than targeting a continuous statistics such as the mean or variance of the values in a bin, the proposed watermarking modifies a discrete statistic, which here is the height of the histogram bin, to achieve watermark embedding. Experimental results demonstrate that the modified algorithm offers not only better resistance against the steganalytic attack we developed, but also an improved robustness/capacity trade-off. }, doi = {10.1109/TVCG.2016.2525771}, url = {http://vic.crs4.it/vic/cgi-bin/bib-page.cgi?id='Yang:2017:3SA'}, }
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