Paper
21 March 2005 Stochastic approach to secret message length estimation in ±k embedding steganography
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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.
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Taras Holotyak, Jessica Fridrich, and David Soukal "Stochastic approach to secret message length estimation in ±k embedding steganography", Proc. SPIE 5681, Security, Steganography, and Watermarking of Multimedia Contents VII, (21 March 2005); https://doi.org/10.1117/12.584201
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Cited by 39 scholarly publications.
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KEYWORDS
Signal to noise ratio

Image analysis

Steganography

Error analysis

Wavelets

Image segmentation

Image processing

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