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Proceedings Paper

Steganalysis of JPEG images using rich models
Author(s): Jan Kodovský; Jessica Fridrich
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Paper Abstract

In this paper, we propose a rich model of DCT coefficients in a JPEG file for the purpose of detecting steganographic embedding changes. The model is built systematically as a union of smaller submodels formed as joint distributions of DCT coefficients from their frequency and spatial neighborhoods covering a wide range of statistical dependencies. Due to its high dimensionality, we combine the rich model with ensemble classifiers and construct detectors for six modern JPEG domain steganographic schemes: nsF5, model-based steganography, YASS, and schemes that use side information at the embedder in the form of the uncompressed image: MME, BCH, and BCHopt. The resulting performance is contrasted with previously proposed feature sets of both low and high dimensionality. We also investigate the performance of individual submodels when grouped by their type as well as the effect of Cartesian calibration. The proposed rich model delivers superior performance across all tested algorithms and payloads.

Paper Details

Date Published: 13 February 2012
PDF: 13 pages
Proc. SPIE 8303, Media Watermarking, Security, and Forensics 2012, 83030A (13 February 2012); doi: 10.1117/12.907495
Show Author Affiliations
Jan Kodovský, Binghamton Univ. (United States)
Jessica Fridrich, Binghamton Univ. (United States)

Published in SPIE Proceedings Vol. 8303:
Media Watermarking, Security, and Forensics 2012
Nasir D. Memon; Adnan M. Alattar; Edward J. Delp III, Editor(s)

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