基于贝叶斯网络群的压缩语音量化索引调制隐写分析方法

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关键词：信息隐藏；隐写分析；压缩语音；贝叶斯网络；支持向量机

中图分类号：TP391 文献标志码：A 文章编号：1671-6841（05）06-0034-08

DOI： 10.13705/j . issn. 1671-6841. 04113

Abstract：To address the problem of low detection accuracy of traditional Bayesian network methods in compressed speech quantization index modulation steganalysis with low embedding rates，a steganalysis method based on Bayesian network ensembles was proposed. Firstly，Bayesian network ensembles were constructed to describe the correlations among speech codewords themselves，within frames，and between frames，and a conditional probability table was built through overall sample learning.Then，the feature vector of individual samples was constructed using the inference results of each sub-network，and these features were used to train a support vector machine（SVM） model. Finally，the steganalysis clasification of unknown samples was achieved. Experimental results showed that on a 1O s Chinese and English speech dataset，with an embedding rate of 20% ，this method improved the detection accuracy by at least 18.01 percentage points and 2.32 percentage points compared with traditional Bayesian network methods and deep learning methods，respectively. Moreover， the average duration for detecting 1 s of speech using this method was 2.72ms ，meeting the requirements for real-time detection.

Key words： steganography； steganalysis ； compressed speech ； Bayesian network ；support vector machine（SVM）

0 引言

随着全球化和信息化的发展，隐私和数据安全问题日益凸显。（剩余12351字）