Blind steganalysis method for BMP images based on statistical MWCF and F-score method

Abstract

As the steganography technology becomes diversified recently, a good blind steganalyzer is in great request. In recent works, a blind steganalysis based on statistical moments of wavelet characteristic functions (MWCF) is proposed, but it has poor generalization ability to some extent. To improve this weakness, the F-score feature selection method is used to filter irrelevant, redundant features calculated from MWCF. By combining MWCF and F-score method, an improved blind steganalysis method is proposed in this article, called FS-MWCF method in short. Experimental results show that the FS-MWCF method has better generalization ability and lower classifying time complexity, less than half of that using MWCF method.