Recognition of PQ stego images based on identifiable statistical feature - Ji-cang LU; Fen-lin LIU; Xiang-yang LUO; Yi ZHANG (Tongxin xuebao)
A PQ (perturbed quantization) stego images recognition algorithm is proposed based on identifiable statistical feature. According to the specific changing ways of PQ steganography to image data, the proposed algorithm extracts the identifiable statistical feature that can distinguish PQ stego images from other types of stego images. Then, the SVM (support vector machines) classifier is trained to recognize PQ stego images. Experimental results show that, the proposed algorithm can reliably recognize PQ stego images from multi-class stego images generated by five types of well-known JPEG steganography (PQ、F5ns、F5、MB1 and MOD). Even though the stego images generated by F5、nsF5、MB1 and MOD are not used for training classifier, the proposed algorithm can still effectively recognize PQ stego images.