Audio steganalysis based on lossless data-compression techniques

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Springer Nature Switzerland AG
In this paper, we introduce a new blind steganalysis method that can reliably detect modifications in audio signals due to steganography. Lossless data-compression ratios are computed from the testing signals and their reference versions and used as features for the classifier design. Additionally, we propose to extract additional features from different energy parts of each tested audio signal to retrieve more informative data and enhance the classifier capability. Support Vector Machine (SVM) is employed to discriminate between the cover- and the stego-audio signals. Experimental results show that our method performs very well and achieves very good detection rates of stego-audio signals produced by S-tools4, Steghide and Hide4PGP. © 2012 Springer-Verlag.
This work is not available in the CUD collection. The version of the scholarly record of this work is published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2012), available online at:
Active speech level, Audio signal, Audio steganalysis, Blind steganalysis, Classifier design, Detection rates, Lossless, Testing signal, Audio signal processing, Steganography, Support vector machines, Data compression
Djebbar, F., Ayad, B. (2012). Audio Steganalysis Based on Lossless Data-Compression Techniques. In T.W. Chim & T.H. Yuen (Eds). Information and Communications Security. ICICS 2012. Lecture Notes in Computer Science, 7618. Springer, Berlin, Heidelberg.