基于邻域像素差分矩阵的彩色空域图像隐写分析特征

doi:10.11959/j.issn.1000-436x.2016042

摘要/Abstract

摘要：

通过分析灰度空域图像隐写直接扩展至彩色空域图像潜在的安全问题，提出了针对彩色空域图像隐写的隐写分析特征。首先，计算颜色通道内邻域像素差分矩阵的 Markov 转移概率矩阵，提取颜色通道内特征并进行融合；然后，计算颜色通道间邻域像素差分矩阵的Markov转移概率矩阵，并将水平和垂直共4个方向与对角和反对角共4个方向的转移概率矩阵分别进行融合，作为颜色通道间特征；最后，颜色通道内特征与颜色通道间特征构成最终的隐写分析特征，并使用集成分类器作为特征训练和测试工具。实验结果表明，该隐写分析特征可有效检测彩色空域图像隐写，并且颜色通道间特征能有效捕获内容自适应隐写对彩色图像的颜色通道间相关性的影响。

关键词: 隐写分析, 彩色空域图像, 内容自适应隐写, 邻域像素差分矩阵, 隐写分析特征

Abstract:

Through analyzing the potential security problems of directly extending steganography based on the grayscale spatial image to the color spatial image, novel steganalysis features for detecting the steganographic methods with color spatial images as cover images were proposed. First of all, the Markov transition probability matr of the subtractive pixel adjacency matrices of three color channels were computed, and then the intra-color-channel features were extracted and merged. Afterwards, the transition probability mat ices of the subtractive pixel adjacency matrices among the color channels were calculated, where four horizontal and vertical directions, and four diagonal and anti-diagonal directions are separately merged. And the two parts composed the inter-color-channel features. Finally, the final feature set of the pro-posed method consists of the intra-color-channel features and the inter-color-channel features, and the ensemble classifier was used for the training and testing of the proposed feature. The experimental results show that the proposed method can effectively detect the steganographic schemes based on the color spatial image. Moreover, the proposed in-ter-color-channel features can efficiently capture the effect of the content-adaptive steganography on the correlation among the color channels of color images.

Key words: steganalysis, color spatial image, content-adaptive steganography, subtractive pixel adjacency matrix, stega-nalysis feature

韩涛,陈熹,祝跃飞. 基于邻域像素差分矩阵的彩色空域图像隐写分析特征[J]. 通信学报, 2016, 37(2): 158-165.

Tao HAN,Xi CHEN,Yue-fei ZHU. Subtractive pixel adjacency matrix based features for steganalysis of spatial color images[J]. Journal on Communications, 2016, 37(2): 158-165.

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P_E	LSBM (0.1 bit/channel pixel)	EALMR (0.4 bit/channel pixel)	WOW (0.4 bit/channel pixel)	S-UNIWARD (0.4 bit/channel pixel)
B-SPAM(Dim 686)	0.303 0	0.333 7	0.437 1	0.445 5
G-SPAM(Dim 686)	0.262 5	0.293 0	0.415 9	0.420 1
R-SPAM(Dim 686)	0.323 4	0.337 2	0.432 1	0.447 6
A-SPAM(Dim 2 058)	0.246 2	0.274 9	0.405 1	0.401 9
M-SPAM(Dim 686)	0.239 0	0.269 9	0.393 6	0.403 3
Gray-SPAM(Dim 686)	0.265 0	0.284 1	0.445 4	0.435 6