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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 paper presents a steganalysis method that estimates the secret key used in sequential steganography. A theory is developed for detecting abrupt jumps in the statistics of the stego signal during steganalysis. Stationary and non-stationary host signals with low, medium and high 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 non-stationary digital image steganalysis are also presented. Extensive experimental results are shown to illustrate the strengths and weaknesses of the proposed steganalysis algorithm.
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Trivedi et al. (2005) studied this question.
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