An Image Steganalysis Method Based on Characteristic Function Moments and PCA
In this paper, a universal steganalysis scheme is proposed for images. The scheme is based on the characteristic function (CF) moments of three-level wavelet subbands including the further decomposition coefficients of the first scale diagonal subband. The first three statistical moments of each wavelet band of test image and prediction-error image are selected to form 102 dimensional features for steganalysis. Principal Components Analysis (PCA) is utilized to reduce the features and the support vector machine (SVM) is adopted as the classifier. The experimental results show the proposed scheme has good performance in attacking JPHide and JSteg.
LI Hui SUN Ziwen ZHOU Zhiping
Institute of Automation, Jiangnan University, Wuxi 214122, P.R.China
国际会议
The 30th Chinese Control Conference(第三十届中国控制会议)
烟台
英文
1-4
2011-07-01（万方平台首次上网日期，不代表论文的发表时间）