Paper
13 February 2012 Steganalysis of JPEG images using rich models
Jan Kodovský, Jessica Fridrich
Author Affiliations +
Proceedings Volume 8303, Media Watermarking, Security, and Forensics 2012; 83030A (2012) https://doi.org/10.1117/12.907495
Event: IS&T/SPIE Electronic Imaging, 2012, Burlingame, California, United States
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.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jan Kodovský and Jessica Fridrich "Steganalysis of JPEG images using rich models", Proc. SPIE 8303, Media Watermarking, Security, and Forensics 2012, 83030A (13 February 2012); https://doi.org/10.1117/12.907495
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Cited by 200 scholarly publications and 1 patent.
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KEYWORDS
Calibration

Steganalysis

Feature extraction

Matrices

Statistical modeling

Performance modeling

Feature selection

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