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Steganalysis of compressed speech to detect covert voice over Internet protocol channels

Huang, Y., Tang, S., Bao, C. and Yip, YJ 2011, 'Steganalysis of compressed speech to detect covert voice over Internet protocol channels' , IET Information Security, 5 (1) , pp. 26-32.

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    A network covert channel is a passage along which information leaks across the network in violation of security policy in a completely undetectable manner. This study reveals our findings in analysing the principle of G.723.1 codec that there are ?unused' bits in G.723.1 encoded audio frames, which can be used to embed secret messages. A novel steganalysis method that employs the second detection and regression analysis is suggested in this study. The proposed method can not only detect the hidden message embedded in a compressed voice over Internet protocol (VoIP) speech, but also accurately estimate the embedded message length. The method is based on the second statistics, that is, doing a second steganography (embedding information in a sampled speech at an embedding rate followed by embedding another information at a different level of data embedding) in order to estimate the hidden message length. Experimental results have proven the effectiveness of the steganalysis method for detecting the covert channel in the compressed VoIP speech.

    Item Type: Article
    Additional Information: This paper is a postprint of a paper submitted to and accepted for publication in IET Information Security and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library
    Themes: Media, Digital Technology and the Creative Economy
    Schools: Colleges and Schools > College of Science & Technology
    Strategic Leadership Team
    Journal or Publication Title: IET Information Security
    Publisher: Institution of Engineering and Technology
    Refereed: Yes
    ISSN: 1751-8709
    Depositing User: Users 29196 not found.
    Date Deposited: 14 Aug 2012 14:07
    Last Modified: 20 Aug 2013 18:30

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