Quantitative structural steganalysis of Jsteg

Quantitative steganalysis strives to estimate the change rate defined as the relative number of embedding changes introduced by steganography. In this paper, we propose two new classes of quantitative steganalysis methods for the steganographic algorithm Jsteg. The first class obtains the change-rate estimate using a maximum likelihood estimator equipped with a precover model. While this approach provides better accuracy than existing structural attacks, it becomes computationally intractable with increasing complexity of the cover model. The second class of methods computes the change-rate estimate by minimizing an objective function constructed from a heuristically formed zero message hypothesis. The advantage of this heuristic approach is a low implementation complexity and modular architecture that allows flexible incorporation of higher order statistics of discrete cosine transform coefficients. The proposed methods are experimentally compared with current state-of-the-art methods.