Universal Steganalysis Using Statistical Manifold Dimension Reduction
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    Abstract:

    Statistical manifold is a manifold of parameterized probability density function. In order to improve steganalysis rate, we propose a using statistical manifold dimension reduction in this paper. The procedure of this algorithm is as follow: first, we use fisher information metric measures the difference among probability density function of image feature vector. Then, we embed characteristics to lower Eucli—dean space by dimension reduction. Finally, we use the support vector machine (SVM) as classifier. The experimental results show that this algorithm is effective to JSteg, F5, MBS1, MBS2 and nsF5 stegano-graphy algorithm.

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戴良斌,全笑梅.运用统计流形降维的通用型隐写分析算法.计算机系统应用,2014,23(9):129-133

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History
  • Received:January 14,2014
  • Revised:February 20,2014
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  • Online: September 18,2014
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