Steganalysis by subtractive pixel adjacency matrix and dimensionality reduction  

作　　者：ZHANG Hao PING XiJian XU ManKun WANG Ran 

机构地区：[1]Department of Signal and Information Processing, Zhengzhou Information Science and Technology Institute

出　　处：《Science China(Information Sciences)》2014年第4期282-288,共7页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China(Grant No.60970142)

摘　　要：Subtractive pixel adjacency matrix （SPAM） features, introduced by Pevn：~ et al. as a type of Markov chain features, are widely used for blind steganalysis in the spatial domain. In this pa.peL we present three improvements to SPAM as follows： 1） new features based on para]lel subtractive pixels are added to the SPAM features, which only refer to collinear subtractive pixels; 2） features are extracted not only from the spatial image, but also from its grayscale-inverted image, making the %ature matrices symmetrical and reducing their dimensionality by about half; and 3） a new kind of adjacency matrix is used, thereby reducing about 3/4 of the dimensionality of the features. Experimental results show that these methods for dimensionality reduction are very effective and that the proposed features outperform SPAM.Subtractive pixel adjacency matrix （SPAM） features, introduced by Pevn：~ et al. as a type of Markov chain features, are widely used for blind steganalysis in the spatial domain. In this pa.peL we present three improvements to SPAM as follows： 1） new features based on para]lel subtractive pixels are added to the SPAM features, which only refer to collinear subtractive pixels; 2） features are extracted not only from the spatial image, but also from its grayscale-inverted image, making the %ature matrices symmetrical and reducing their dimensionality by about half; and 3） a new kind of adjacency matrix is used, thereby reducing about 3/4 of the dimensionality of the features. Experimental results show that these methods for dimensionality reduction are very effective and that the proposed features outperform SPAM.

关 键 词：STEGANALYSIS Markov chain dimensionality reduction LSB matching YASS algorithnl 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] O157.5[自动化与计算机技术—计算机科学与技术]