Image steganalysis based on convolutional neural network and feature selection

被引:2
作者
Sun, Zhanquan [1 ,4 ]
Lie, Feng [2 ]
Huang, Huifen [3 ]
Wang, Jian [4 ]
机构
[1] Univ Shanghai Sci & Technol, Sch Opt Elect & Comp Engn, Shanghai Key Lab Modern Opt Syst, Engn Res Ctr Opt Instrument & Syst,Minist Educ, Shanghai 200093, Peoples R China
[2] Shanghai Univ, Coll Liberal Arts, Dept Hist, Shanghai, Peoples R China
[3] Shandong Yingcai Univ, Jinan, Shandong, Peoples R China
[4] China Univ Petr, Coll Sci, Qingdao 266580, Shandong, Peoples R China
基金
美国国家科学基金会;
关键词
convolutional neural network; feature selection; image steganalysis; MapReduce; wavelet transformation; DEEP BELIEF NETWORKS;
D O I
10.1002/cpe.5469
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Steganalysis is to detect whether or not the seemly innocent image hiding message. It is an important research topic in information security. With the development of steganography technology, steganalysis becomes more and more difficult. Some steganalysis methods have been proposed to improve the performance. Most research work concentrates on special steganography information detection and the image steganography features are designed manually. Few research works concentrate on universal steganalysis methods. In this paper, as the first several attempts, a novel image steganalysis method based on deep neural network is proposed. First, image high-frequency features are extracted with wavelet transformation method because that most image hiding message are high frequency. Second, high-dimensional image steganography features are extracted with deep neural networks according to the high-frequency images and informative features combination is selected with a novel feature selection method based on entropy. Then, a parallel SVM model is proposed to build the steganalysis model based on large scale training samples. At last, the efficiency of the proposed method is illustrated through analyzing a practical image steganalysis example.
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页数:10
相关论文
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