Multi-class JPEG Image Steganalysis by Ensemble Linear SVM Classifier

Multi-class steganalysis utilizes multi-class classification methods to predict the category of steganographic schemes used for generating stego files. In this paper we propose a novel multi-class approach towards more efficiently classifying JPEG stego-images with CC-JRM features. Because CC-JRM has successfully cooperates with ensemble classifier in detecting the presence of stego images, we modified ensemble classifier for multi-class steganalysis. The ideas of performing ensemble in different steps results in two schemes in our proposed method. These two schemes are based on different multi-class ensemble strategies, and utilize linear SVM as base classifier. The experimental results shows our methods received better results with less computing cost compared to other multi-class steganalysis method.