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Distributed steganalysis of compressed speech

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Abstract

In this paper, we present a distributed steganalysis scheme for compressed speech in voice-over-IP scenarios to provide fast and precise detection results. In this scheme, each speech parameter available for concealing information is designed to be detected independently exploiting the corresponding optimal detection feature. To achieve this purpose, we introduce four detection features, including histogram distribution, differential histogram distribution, Markov transition matrix and differential Markov transition matrix. These features stem from both long-time distribution characteristics and short-time invariance characteristics of speech signals. We evaluate their performance for steganalysis based on support vector machines with a large number of steganographic G.729a speech samples at different embedding rates or with various sample lengths and compare them with some existing algorithms. The experimental results demonstrate that the presented algorithms can offer excellent steganalysis performance for all speech parameters in any case and outperform the previous ones. Moreover, it is proved that the four features have diverse performance for steganalysis of different speech parameters, which suggests that it is feasible to achieve the distributed steganalysis employing the optimal feature to detect the corresponding parameter in a faster and more efficient manner.

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Acknowledgments

This work was supported in part by Natural Science Foundation of China under Grant Nos. 61302094, U1405254, 61370007 and 61202468, Natural Science Foundation of Fujian Province of China under Grant No. 2014J01238, Education and Science Research Program for Young and Middle-aged Teacher of Fujian Province of China under Grant No. JA13012, Promotion Program for Young and Middle-aged Teacher in Science and Technology Research of Huaqiao University under Grant No. ZQN-PY115, Fundamental Research Funds for the Central Universities under Grant No. 14BS210 and Program for Science and Technology Innovation Teams and Leading Talents of Huaqiao University under Grant No. 2014KJTD13.

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Authors and Affiliations

  1. College of Computer Science and Technology, National Huaqiao University, Xiamen, 361021, China

    Hui Tian, Yanpeng Wu, Yiqiao Cai, Jin Liu, Tian Wang & Yonghong Chen

  2. Department of Electronic Engineering, Tsinghua University, Beijing, 100084, China

    Yongfeng Huang

  3. Department of Information Management, National Huaqiao University, Xiamen, 361021, China

    Jing Lu

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  1. Hui Tian
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  2. Yanpeng Wu
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  3. Yiqiao Cai
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  4. Yongfeng Huang
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  5. Jin Liu
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  6. Tian Wang
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  7. Yonghong Chen
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  8. Jing Lu
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Correspondence to Hui Tian.

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Communicated by V. Loia.

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Tian, H., Wu, Y., Cai, Y. et al. Distributed steganalysis of compressed speech. Soft Comput 21, 795–804 (2017). https://doi.org/10.1007/s00500-015-1816-0

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