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Steganalysis of Compressed Speech Based on Markov and Entropy

  • Haibo Miao
  • Liusheng Huang
  • Yao Shen
  • Xiaorong Lu
  • Zhili Chen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8389)

Abstract

Compressed domain based steganography (CDBS) is a kind of relatively new and secure audio steganography. Up to date, there is little research on the steganalysis against this kind of audio steganography. In this paper, we introduce two methods to detect various CDBS on ACELP speech. One is the Markov method and the other is the entropy method. Both methods are based on the observation that the steganography behavior has certain effects on the relationship among the pulses in the same track. The Markov transition probabilities are utilized to evaluate the interrelationships between adjacent pulses and entropy is employed to measure the “disorder” of combined pulse distributions. First, Markov transition probabilities, joint entropy and conditional entropy features of the track pulses are extracted; a support vector machine (SVM) is then applied to the features for discovering the existence of hidden data in compressed speech signals, respectively. Some famous CDBS methods on ACELP encoded speech are considered. Experimental results have proven the effectiveness of the two methods.

Keywords

Steganalysis Compressed speech Markov Entropy SVM CDBS 

Notes

Acknowledgement

This work is supported by the National Natural Science Foundation of China (No. 61202407), the Fundamental Research Funds for the Central Universities (No. WK0110000033 & No.WK0110000027), the Natural Science Foundation of Jiangsu Province of China (No. BK2011357) and the Guangdong Province Strategic Cooperation Project with the Chinese Academy of Sciences (No. 2012B090400013).

The authors would like to thank the anonymous reviewers for their helpful comments and suggestions.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Haibo Miao
    • 1
    • 2
  • Liusheng Huang
    • 1
    • 2
  • Yao Shen
    • 1
    • 2
  • Xiaorong Lu
    • 1
    • 2
  • Zhili Chen
    • 1
    • 2
  1. 1.NHPCC, Department of Computer Science and TechnologyUSTCHefeiChina
  2. 2.Suzhou Institute for Advanced StudyUSTCSuzhouChina

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