Markov bidirectional transfer matrix for detecting LSB speech steganography with low embedding rates
Markov bidirectional transfer matrix for detecting LSB speech steganography with low embedding rates
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用于检测低嵌入率 LSB 语音隐写术的马尔可夫双向传输矩阵
DOI：
10.1007/s11042-017-5505-0
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发表时间：
2018-01
期刊：
影响因子：
--
通讯作者：
Miaoqi Li
中科院分区：
文献类型：
--
作者：
WanxiaYang;Shanyu Tang;Miaoqi Li
低嵌入率的隐写分析在信息隐藏领域仍然是一个挑战。语音信号通常通过小波包分解进行处理，它能够高精度地描述信号的细节。一种隐写术
Steganalysis with low embedding rates is still a challenge in the field of information hiding. Speech signals are typically processed by wavelet packet decomposition, which is capable of depicting the details of signals with high accuracy. A steganography detection algorithm based on the Markov bidirectional transition matrix (MBTM) of the wavelet packet coefficient (WPC) of the second-order derivative-based speech signal is proposed. On basis of the MBTM feature, which can better express the correlation of WPC, a Support Vector Machine (SVM) classifier is trained by a large number of Least Significant Bit (LSB) hidden data with embedding rates of 1%, 3%, 5%, 8%,10%, 30%, 50%, and 80%. LSB matching steganalysis of speech signals with low embedding rates is achieved. The experimental results show that the proposed method has obvious superiorities in steganalysis with low embedding rates compared with the classic method using histogram moment features in the frequency domain (HMIFD) of the second-order derivative-based WPC and the second-order derivative-based Mel-frequency cepstral coefficients (MFCC). Especially when the embedding rate is only 3%, the accuracy rate improves by 17.8%, reaching 68.5%, in comparison with the method using HMIFD features of the second derivative WPC. The detection accuracy improves as the embedding rate increases.
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DOI：
10.1109/tcsvt.2012.2224052
发表时间：
2013-07
影响因子：
8.4
作者：
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DOI：
10.1631/jzus.c1100374
发表时间：
2012-08
期刊：
Journal of Zhejiang University: Science C
影响因子：
--
作者：
Song-bin LI 1;Beijing 100084;China);Song-bin LI 1,2,Huai-zhou TAO1,2,Yong-feng HUANG 1;2;Huai-zhou TAO1;2;Yong-feng HUANG 1;2(1Department of Electronic Engineering;Tsinghua University;Beijing 100084;China)(2Tsinghua National Laboratory for Informati
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China)(2Tsinghua National Laboratory for Informati
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7.8
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10.1109/tifs.2015.2423656
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影响因子：
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