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Proceedings Paper

Stochastic approach to secret message length estimation in ±k embedding steganography
Author(s): Taras Holotyak; Jessica Fridrich; David Soukal
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Paper Abstract

In this paper, we propose a new method for estimation of the number of embedding changes for non-adaptive ±k embedding in images. By modeling the cover image and the stego noise as additive mixture of random processes, the stego message is estimated from the stego image using a denoising filter in the wavelet domain. The stego message estimate is further analyzed using ML/MAP estimators to identify the pixels that were modified during embedding. For non-adaptive ±k embedding, the density of embedding changes is estimated from selected segments of the stego image. It is shown that for images with a low level of noise (e.g., for decompressed JPEG images) this approach can detect and estimate the number of embedding changes even for small values of k, such as k=2, and in some cases even for k=1.

Paper Details

Date Published: 21 March 2005
PDF: 12 pages
Proc. SPIE 5681, Security, Steganography, and Watermarking of Multimedia Contents VII, (21 March 2005); doi: 10.1117/12.584201
Show Author Affiliations
Taras Holotyak, State Univ. of New York/Binghamton (United States)
Jessica Fridrich, State Univ. of New York/Binghamton (United States)
David Soukal, State Univ. of New York/Binghamton (United States)


Published in SPIE Proceedings Vol. 5681:
Security, Steganography, and Watermarking of Multimedia Contents VII
Edward J. Delp; Ping W. Wong, Editor(s)

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