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Proceedings Paper

New blind steganalysis and its implications
Author(s): Miroslav Goljan; Jessica Fridrich; Taras Holotyak
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Paper Abstract

The contribution of this paper is two-fold. First, we describe an improved version of a blind steganalysis method previously proposed by Holotyak et al. and compare it to current state-of-the-art blind steganalyzers. The features for the blind classifier are calculated in the wavelet domain as higher-order absolute moments of the noise residual. This method clearly shows the benefit of calculating the features from the noise residual because it increases the features' sensitivity to embedding, which leads to improved detection results. Second, using this detection engine, we attempt to answer some fundamental questions, such as "how much can we improve the reliability of steganalysis given certain a priori side-information about the image source?" Moreover, we experimentally compare the security of three steganographic schemes for images stored in a raster format - (1) pseudo-random ±1 embedding using ternary matrix embedding, (2) spatially adaptive ternary ±1 embedding, and (3) perturbed quantization while converting a 16-bit per channel image to an 8-bit gray scale image.

Paper Details

Date Published: 15 February 2006
PDF: 13 pages
Proc. SPIE 6072, Security, Steganography, and Watermarking of Multimedia Contents VIII, 607201 (15 February 2006); doi: 10.1117/12.643254
Show Author Affiliations
Miroslav Goljan, SUNY Binghamton (United States)
Jessica Fridrich, SUNY Binghamton (United States)
Taras Holotyak, SUNY Binghamton (United States)


Published in SPIE Proceedings Vol. 6072:
Security, Steganography, and Watermarking of Multimedia Contents VIII
Edward J. Delp III; Ping Wah Wong, Editor(s)

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