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Proceedings Paper

Steganalysis using color wavelet statistics and one-class support vector machines
Author(s): Siwei Lyu; Hany Farid
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Paper Abstract

Steganographic messages can be embedded into digital images in ways that are imperceptible to the human eye. These messages, however, alter the underlying statistics of an image. We previously built statistical models using first-and higher-order wavelet statistics, and employed a non-linear support vector machines (SVM) to detect steganographic messages. In this paper we extend these results to exploit color statistics, and show how a one-class SVM greatly simplifies the training stage of the classifier.

Paper Details

Date Published: 22 June 2004
PDF: 11 pages
Proc. SPIE 5306, Security, Steganography, and Watermarking of Multimedia Contents VI, (22 June 2004); doi: 10.1117/12.526012
Show Author Affiliations
Siwei Lyu, Dartmouth College (United States)
Hany Farid, Dartmouth College (United States)


Published in SPIE Proceedings Vol. 5306:
Security, Steganography, and Watermarking of Multimedia Contents VI
Edward J. Delp; Ping W. Wong, Editor(s)

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