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Front. Inform. Technol. Electron. Eng.  2012, Vol. 13 Issue (8): 624-634    DOI: 10.1631/jzus.C1100374
    
Detection of quantization index modulation steganography in G.723.1 bit stream based on quantization index sequence analysis
Song-bin Li, Huai-zhou Tao, Yong-feng Huang
Department of Electronic Engineering, Tsinghua University, Beijing 100084, China; Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, China
Detection of quantization index modulation steganography in G.723.1 bit stream based on quantization index sequence analysis
Song-bin Li, Huai-zhou Tao, Yong-feng Huang
Department of Electronic Engineering, Tsinghua University, Beijing 100084, China; Tsinghua National Laboratory for Information Science and Technology, Beijing 100084, China
 全文: PDF 
摘要: This paper presents a method to detect the quantization index modulation (QIM) steganography in G.723.1 bit stream. We show that the distribution of each quantization index (codeword) in the quantization index sequence has unbalanced and correlated characteristics. We present the designs of statistical models to extract the quantitative feature vectors of these characteristics. Combining the extracted vectors with the support vector machine, we build the classifier for detecting the QIM steganography in G.723.1 bit stream. The experiment shows that the method has far better performance than the existing blind detection method which extracts the feature vector in an uncompressed domain. The recall and precision of our method are all more than 90% even for a compressed bit stream duration as low as 3.6 s.
关键词: SteganalysisQuantization index modulation (QIM)G.723.1Codeword distribution characteristics    
Abstract: This paper presents a method to detect the quantization index modulation (QIM) steganography in G.723.1 bit stream. We show that the distribution of each quantization index (codeword) in the quantization index sequence has unbalanced and correlated characteristics. We present the designs of statistical models to extract the quantitative feature vectors of these characteristics. Combining the extracted vectors with the support vector machine, we build the classifier for detecting the QIM steganography in G.723.1 bit stream. The experiment shows that the method has far better performance than the existing blind detection method which extracts the feature vector in an uncompressed domain. The recall and precision of our method are all more than 90% even for a compressed bit stream duration as low as 3.6 s.
Key words: Steganalysis    Quantization index modulation (QIM)    G.723.1    Codeword distribution characteristics
收稿日期: 2011-12-19 出版日期: 2012-08-02
CLC:  TN918  
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Song-bin Li, Huai-zhou Tao, Yong-feng Huang. Detection of quantization index modulation steganography in G.723.1 bit stream based on quantization index sequence analysis. Front. Inform. Technol. Electron. Eng., 2012, 13(8): 624-634.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1100374        http://www.zjujournals.com/xueshu/fitee/CN/Y2012/V13/I8/624

[1] Hong-yuan Chen, Yue-sheng Zhu. A robust watermarking algorithm based on QR factorization and DCT using quantization index modulation technique[J]. Front. Inform. Technol. Electron. Eng., 2012, 13(8): 573-584.