Secret key estimation in sequential steganography

We define sequential steganography as those class of embedding algorithms that hide messages in consecutive (time, spatial, or frequency domain) features of a host signal. This work presents a steganalysis method that estimates the secret key used in sequential embedding. Steganalysis is posed as the detection of abrupt jumps in the statistics of a stego signal. Stationary and nonstationary host signals with low, medium, and high signal-to-noise ratio (SNR) embedding are considered. A locally most powerful steganalysis detector for the low SNR case is also derived. Several techniques to make the steganalysis algorithm work for nonstationary digital image steganalysis are also presented. Extensive experimental results are shown to illustrate the strengths and weaknesses of the proposed steganalysis algorithm.