Breaking Cauchy Model-Based JPEG Steganography with First Order Statistics

The recent approach of a model-based framework for steganography fruitfully contributes to the discussion on the security of steganography. In addition, the first proposal for an embedding algorithm constructed under the model-based paradigm reached remarkable performance in terms of capacity and security. In this paper, we review the emerging of model-based steganography in the context of decent steganalysis as well as from theoretical considerations, before we present a method to attack the above-mentioned scheme on the basis of first order statistics. Experimental results show a good detection ratio for a large test set of typical JPEG images. The attack is successful because of weaknesses in the model and does not put into question the generalised theoretical framework of model-based steganography. So we discuss possible implications for improved embedding functions.