Image steganalysis algorithm based on feature ranking

被引：0

作者：

Zhang Xing-chun ^{[1
]}

Sun Shou-jian ^{[2
,3
]}

机构：

[1] Command Heilongjiang Crops PAP, Harbin 150000, Heilongjiang, Peoples R China

[2] Heilongjiang Crops PAP, Command Jiamusi Detachment, Jiamusi 154000, Peoples R China

[3] Engn Univ PAP, Network & Informat Secur Key Lab PAP, Xian 710086, Shaanxi, Peoples R China

来源：

CHINESE JOURNAL OF LIQUID CRYSTALS AND DISPLAYS | 2018年 / 33卷 / 06期

基金：

中国国家自然科学基金;

关键词：

steganalysis; ensemble classifier; feature ranking; mutual information scores;

D O I：

10.3788/YJYXS20183306.0490

中图分类号：

O7 [晶体学];

学科分类号：

0702 ; 070205 ; 0703 ; 080501 ;

摘要：

In order to enhance the detection rate of ensemble classifier, an algorithm based on feature ranking is proposed. First, the original feature is sorted according mutual information score. Then the sorted feature is divided into important feature part and common feature part according to the divide point. The feature subset is formed by selecting features randomly in each part according to the given sampling rate. Experimental results show that, our method detects two format images after embedding nsF5 and S-UNIWARD, the false detection is lower than classical ensemble classifier 0. 0065 to .jpeg images, and the false detection is lower than 0.0062 to .bmp images. Compared with typical ensemble classifier, the proposed method is more effective than the different stego algorithms in frequency domain and spatial domain.

引用

页码：490 / 496

页数：7

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