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Proceedings Paper

Blind source separation for steganalytic secret message estimation
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Paper Abstract

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.

Paper Details

Date Published: 27 February 2007
PDF: 6 pages
Proc. SPIE 6505, Security, Steganography, and Watermarking of Multimedia Contents IX, 650507 (27 February 2007); doi: 10.1117/12.704726
Show Author Affiliations
Aruna Ambalavanan, Stevens Institute of Technology (United States)
R. Chandramouli, Stevens Institute of Technology (United States)

Published in SPIE Proceedings Vol. 6505:
Security, Steganography, and Watermarking of Multimedia Contents IX
Edward J. Delp III; Ping Wah Wong, Editor(s)

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