INFORMATION CHANGE THE WORLD

International Journal of Computer Network and Information Security(IJCNIS)

ISSN: 2074-9090 (Print), ISSN: 2074-9104 (Online)

Published By: MECS Press

IJCNIS Vol.4, No.11, Oct. 2012

Feature Based Audio Steganalysis (FAS)

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Author(s)

Souvik Bhattacharyya,Gautam Sanyal

Index Terms

Audio Steganalysis; Statistical Moments; Invariant Moments; SVM Classifier; KNN Classifier

Abstract

Taxonomy of audio signals containing secret information or not is a security issue addressed in the context of steganalysis. A cover audio object can be converted into a stego-audio object via different steganographic methods. In this work the authors present a statistical method based audio steganalysis technique to detect the presence of hidden messages in audio signals. The conceptual idea lies in the difference of the distribution of various statistical distance measures between the cover audio signals and their denoised versions i.e. stego-audio signals. The design of audio steganalyzer relies on the choice of these audio quality measures and the construction of two-class classifier based on KNN (k nearest neighbor), SVM (support vector machine) and two layer Back Propagation Feed Forward Neural Network (BPN). Experimental results show that the proposed technique can be used to detect the small presence of hidden messages in digital audio data. Experimental results demonstrate the effectiveness and accuracy of the proposed technique.

Cite This Paper

Souvik Bhattacharyya,Gautam Sanyal,"Feature Based Audio Steganalysis (FAS)", IJCNIS, vol.4, no.11, pp.62-73,2012.

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