Fusion of Two Typical Quantitative Steganalysis Based on SVR

摘要

For the LSB steganography, a fusion method is proposed to fuse two typical quantitative steganalysis methods based on support vector regression (SVR). This paper first gives some main factors influencing the errors of structural steganalysis and weighted stego image steganalysis, viz. the local variance and saturation. Then, the estimated embedding ratios of above two methods, the local variance, the histogram of local variance and saturation are fed to the SVR to train the fusion rule which is used to fusing these two methods. Experimental results show that the proposed fusion method can estimate the embedding ratio with higher accuracy than the individual method.