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Pattern Recognition, International Conference on (2010)
Istanbul, Turkey
Aug. 23, 2010 to Aug. 26, 2010
ISSN: 1051-4651
ISBN: 978-0-7695-4109-9
pp: 4376-4379
Most work on steganalysis, except a few exceptions, have primarily focused on providing features with high discrimination power without giving due consideration to issues concerning practical deployment of steganalysis methods. In this work, we focus on machine learning aspect of steganalyzer design and utilize a hierarchical ensemble of classifiers based approach to tackle two main issues. Firstly, proposed approach provides a workable and systematic procedure to incorporate several steganalyzers together in a composite steganalyzer to improve detection performance in a scalable and cost-effective manner. Secondly, since the approach can be readily extended to multi-class classification it can also be used to infer the steganographic technique deployed in generation of a stego-object. We provide results to demonstrate the potential of the proposed approach.
classifier fusion, steganalysis, steganography, ensemble of classifiers

N. Memon, A. E. Dirik, S. Bayram and H. T. Sencar, "An Ensemble of Classifiers Approach to Steganalysis," 2010 20th International Conference on Pattern Recognition (ICPR 2010)(ICPR), Istanbul, 2010, pp. 4376-4379.
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