Paper
10 February 2011 Feature restoration and distortion metrics
Ventsislav K. Chonev, Andrew D. Ker
Author Affiliations +
Proceedings Volume 7880, Media Watermarking, Security, and Forensics III; 78800G (2011) https://doi.org/10.1117/12.872574
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States
Abstract
Our work focuses on Feature Restoration (FR), a technique which may be used in conjunction with steganographic schemes to reduce the likelihood of detection by a steganalyzer. This is done by selectively modifying the stego image to reduce a given distortion metric to a chosen target feature vector. The technique is independent of the exact steganographic algorithm used and can be applied with respect to any set of steganalytic features and any distortion metric. The general FR problem is NP-complete and hence intractable, but randomized algorithms are able to achieve good approximations. However, the choice of distortion metric is crucial: our results demonstrate that, for a poorly chosen metric or target, reducing the distortion frequently leads to an increased likelihood of detection. This has implications for other distortion-reduction schemes.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ventsislav K. Chonev and Andrew D. Ker "Feature restoration and distortion metrics", Proc. SPIE 7880, Media Watermarking, Security, and Forensics III, 78800G (10 February 2011); https://doi.org/10.1117/12.872574
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Cited by 9 scholarly publications.
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KEYWORDS
Distortion

Detection and tracking algorithms

Mahalanobis distance

Image restoration

Sensors

Computer programming

Steganalysis

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