中国邮电高校学报(英文) ›› 2007, Vol. 14 ›› Issue (3): 103-107.doi: 1005-8885 (2007) 03-0103-05

• Signal processing • 上一篇    下一篇

LSB steganalysis of speech data based on distance measure and ML decision

邓宗元;劭羲;杨震   

  1. Institute of Signal and Information Processing, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • 收稿日期:2006-12-22 修回日期:1900-01-01 出版日期:2007-09-30

LSB steganalysis of speech data based on distance measure and ML decision

DENG Zong-yuan; SHAO Xi; YANG Zhen   

  1. Institute of Signal and Information Processing, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
  • Received:2006-12-22 Revised:1900-01-01 Online:2007-09-30

摘要:

Steganalysis can be used to classify an object whether or not it contains hidden information. In this article, is presented, a novel approach to detect the presence of least significant bit (LSB) steganographic messages in the voice secure communication system. A distance measure, which has proven to be sensitive to LSB steganography by analysis of variance (ANOVA), is denoted to estimate the difference between the host signal and the stego signal. Then an maximum likelihood (ML) decision is combined to form the classifier. Statistical experiments show that the proposed approach has a highly accurate rate and low computational complexity.

关键词:

speech signal processing; LSB steganography; steganalysis; ML decision

Abstract:

Steganalysis can be used to classify an object whether or not it contains hidden information. In this article, is presented, a novel approach to detect the presence of least significant bit (LSB) steganographic messages in the voice secure communication system. A distance measure, which has proven to be sensitive to LSB steganography by analysis of variance (ANOVA), is denoted to estimate the difference between the host signal and the stego signal. Then an maximum likelihood (ML) decision is combined to form the classifier. Statistical experiments show that the proposed approach has a highly accurate rate and low computational complexity.

Key words:

speech signal processing; LSB steganography; steganalysis; ML decision

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