运用统计流形降维的通用型隐写分析算法  

Universal Steganalysis Using Statistical Manifold Dimension Reduction

作　　者：戴良斌 全笑梅[1] 

机构地区：[1]北京工业大学计算机学院,北京100124

出　　处：《计算机系统应用》2014年第9期129-133,共5页Computer Systems & Applications

摘　　要：统计流形是参数化概率密度函数组成的流形,将统计流形引入到隐写分析中.根据图像特征向量的概率密度函数,将Fisher信息距离作为差异度量标准,然后通过降维将特征嵌入低维欧式空间并采用支持向量机作为分类器.实验结果表明该算法对JSteg,F5,MBS1,MBS2,nsF5等隐写算法都有较好的识别效果.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.

关 键 词：隐写分析 统计流形 降维 特征向量 Fisher信息距离 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]