Search:
Computing and Library Services - delivering an inspiring information environment

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

Huang, Y., Tang, S., Bao, C. and Yip, Yau Jim (2011) Steganalysis of compressed speech to detect covert voice over Internet protocol channels. IET Information Security, 5 (1). pp. 26-32. ISSN 17518709

[img]
Preview
PDF - Accepted Version
Download (283kB) | Preview

Abstract

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
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
U Military Science > U Military Science (General)
Schools: School of Computing and Engineering
School of Computing and Engineering > High-Performance Intelligent Computing
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
Related URLs:
Depositing User: Graham Stone
Date Deposited: 10 May 2011 08:26
Last Modified: 21 Aug 2015 10:05
URI: http://eprints.hud.ac.uk/id/eprint/10315

Downloads

Downloads per month over past year

Repository Staff Only: item control page

View Item View Item

University of Huddersfield, Queensgate, Huddersfield, HD1 3DH Copyright and Disclaimer All rights reserved ©