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Proceedings Paper

The impact of information fusion in steganalysis on the example of audio steganalysis
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Paper Abstract

Information fusion tries to determine the best set of experts in a given problem domain and devise an appropriate function that can optimally combine the decisions of the individual experts. Only few systematic approaches to information fusion exist so far in the signal processing field of steganalysis. Under the basic assumption that steganalysis can be seen as a statistical pattern recognition process like biometrics, a state of the art five level information fusion model known from biometrics is transferred to steganalysis as well as statistical detectability evaluations for watermarking algorithms and its applicability is evaluated in practical testing. The primary test goal for these evaluations is to measure the impact of fusion on the classification accuracy. Therefore a match and decision level fusion are performed here for three selected data hiding algorithms (one steganography and two watermarking), two feature extractors and five different classifiers. For the test heterogeneous audio test sets are used for content independent training and testing. The secondary test goal of this work is to consider the impact of the key selection assumption on the accuracy of the classification in steganalysis. The results show for the test cases an increase of the classification accuracy for two of the three tested algorithms by match level fusions, no gain by decision level fusion and a considerably small impact of the key selection assumption on the statistical detectability.

Paper Details

Date Published: 4 February 2009
PDF: 12 pages
Proc. SPIE 7254, Media Forensics and Security, 725409 (4 February 2009); doi: 10.1117/12.805884
Show Author Affiliations
Christian Kraetzer, Otto-von-Guericke Univ. of Magdeburg (Germany)
Jana Dittmann, Otto-von-Guericke Univ. of Magdeburg (Germany)

Published in SPIE Proceedings Vol. 7254:
Media Forensics and Security
Edward J. Delp III; Jana Dittmann; Nasir D. Memon; Ping Wah Wong, Editor(s)

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