摘要: 提出一种能够有效检测含密JPEG图像的掩密分析方法,利用图像的一阶和二阶统计特征分别提取原始图像和掩密图像的直方图特征以及图像块内和块间的部分统计特征,采用支持向量机对原始图像和掩密图像的特征进行训练、分类并建立模型,达到通用检测的目的。实验结果表明,该算法能够对Jsteg, F5, OutGuess和MB等掩密算法进行有效分析。
关键词:
掩密术,
掩密分析,
统计特征,
支持向量机
Abstract: This paper presents a steganalysis scheme which can effectively attack JPEG steganographic. The method exploits the first and the second order statistic characteristics. It extracts these characteristics of histogram and the partial statistical characteristics of intra-block and inter-block from the cover-images and the stego-images respectively. In order to achieve the purpose of general detection, it uses Support Vector Machine(SVM) to train and distinguish these characteristics, and establishs the model. Experimental results show that the method performs well in steganalysis methods such as Jsteg, F5, OutGuess, and MB.
Key words:
steganography,
steganalysis,
statistic characteristic,
Support Vector Machine(SVM)
中图分类号:
贵 琦;柏 森;孙 静. 基于统计特征和SVM的JPEG图像掩密分析[J]. 计算机工程, 2008, 34(8): 141-143.
GUI Qi; BAI Sen; SUN Jing. JPEG Images Steganalysis Based on Statistic Characteristic and SVM[J]. Computer Engineering, 2008, 34(8): 141-143.