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Proceedings Paper

System approach to steganalysis
Author(s): Josef D. Allen; Sereyvathana Ty; Xiuwen Liu
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Paper Abstract

Digital steganographic algorithms hide secret messages in seemingly innocent cover objects, such as images. Steganographic algorithms are rapidly evolving, reducing distortions, and making detection of altered cover objects by steganalysis algorithms more challenging. The value of current steganographic and steganalysis algorithms is difficult to evaluate until they are tested on realistic datasets. We propose a system approach to steganalysis for reliably detecting steganographic objects among a large number of images, acknowledging that most digital images are intact. The system consists of a cascade of intrinsic image formations filters (IIFFs), where the IIFFs in the early stage are designed to filter out non-stego images based on real world constraints, and the IIFFs in the late stage are designed to detect intrinsic features of specific steganographic routines. Our approach makes full use of all available constraints, leading to robust detection performance and low probability of false alarm. Our results based on a large image set from demonstrate the potential of our approach on large-scale real-world repositories.

Paper Details

Date Published: 31 May 2011
PDF: 8 pages
Proc. SPIE 8063, Mobile Multimedia/Image Processing, Security, and Applications 2011, 80630P (31 May 2011); doi: 10.1117/12.884353
Show Author Affiliations
Josef D. Allen, Oak Ridge National Lab. (United States)
The Florida State Univ. (United States)
Sereyvathana Ty, The Florida State Univ. (United States)
Xiuwen Liu, The Florida State Univ. (United States)

Published in SPIE Proceedings Vol. 8063:
Mobile Multimedia/Image Processing, Security, and Applications 2011
Sos S. Agaian; Sabah A. Jassim; Yingzi Du, Editor(s)

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