郑州大学学报（理学版）2025，Vol.57Issue(6)：34-41,8.DOI:10.13705/j.issn.1671-6841.2024113
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
Steganalysis Based on Bayesian Network Ensembles for Compressed Speech Quantization Index Modulation
摘要
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 classifica-tion of unknown samples was achieved.Experimental results showed that on a 10 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 2.72 ms,meeting the requirements for real-time detection.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Key words
steganography/steganalysis/compressed speech/Bayesian network/support vector machine(SVM)分类
信息技术与安全科学引用本文复制引用
高飞鹏,杨洁..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[J].郑州大学学报（理学版）,2025,57(6):34-41,8.基金项目
浙江省自然科学基金项目(LQ20F020004) （LQ20F020004）
