27 February 2007 Blind source separation for steganalytic secret message estimation
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A blind source separation method for steganalysis of linear additive embedding techniques is presented. The paper formulates steganalysis as a blind source separation problem -- statistically separate the host and secret message carrying signals. A probabilistic model of the source distributions is defined based on its sparsity. The problem of having fewer observations than the number of sources is effectively handled exploiting the sparsity and a maximum a posteriori probability (MAP) estimator is developed to chose the best estimate of the sources. Experimental details are provided for steganalysis of a discrete cosine transform (DCT) domain data embedding technique.
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Aruna Ambalavanan, Aruna Ambalavanan, R. Chandramouli, R. Chandramouli, "Blind source separation for steganalytic secret message estimation", Proc. SPIE 6505, Security, Steganography, and Watermarking of Multimedia Contents IX, 650507 (27 February 2007); doi: 10.1117/12.704726; https://doi.org/10.1117/12.704726

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