Result Analysis of Cross-Validation on low embedding Feature-based Blind Steganalysis of 25 percent on JPEG images using SVM

This paper presents a result analysis of steganalysis of normal JPEG images as compared to the images that have undergone a cross-validation. Four different algorithms, in spatial and transform domain is used for steganography. They are LSB Matching, LSB Replacement, Pixel Value Differencing and F5. The embedding percentage considered in this paper is 25. The features considered for analysis are First Order features, Second Order features, Extended DCT features and Markov features. The classifier used here is Support Vector Machine. A different sampling of data is considered for classification.