Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/5569
Title: An ensemble of classifiers approach to steganalysis
Authors: Bayram S.
Dirik A. E.
Sencar, Hüsrev Taha
Memon, Nasir
Issue Date: 2010
Source: 2010 20th International Conference on Pattern Recognition, ICPR 2010, 23 August 2010 through 26 August 2010, Istanbul, 82392
Abstract: 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. © 2010 IEEE.
URI: https://doi.org/10.1109/ICPR.2010.1064
https://hdl.handle.net/20.500.11851/5569
ISBN: 9780769541099
ISSN: 1051-4651
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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