Steganalysis of Low Embedding Rates LSB Speech Based on Histogram Moments in Frequency Domain ∗
Steganalysis of Low Embedding Rates LSB Speech Based on Histogram Moments in Frequency Domain ∗
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基于频域直方图矩的低嵌入率 LSB 语音隐写分析 —
DOI：
10.1049/cje.2017.09.026
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发表时间：
2017
影响因子：
1.2
通讯作者：
LI Miaoqi
中科院分区：
文献类型：
--
作者：
YANG Wanxia;TANG Shanyu;LI Miaoqi
由于小波包变换能够关注信号的微小变化，本研究提出了一种基于频域高阶直方图矩（HMFD）的低嵌入隐写分析方法，为HMFD的特征选择和提取提供了关键解决方案。分别用语音信号中不同嵌入率的LSB匹配隐写术对检测结果进行测试，证明HMFD的检测性能优于直方图统计矩的检测性能。 HMFD通过小波包分解(WPD)可以有效检测低嵌入率的最低有效位(LSB)语音隐写术，其准确率可以达到60.8%，而嵌入率仅为3%。
As wavelet packet transform is able to focus on minute change of signals, this study proposes an analytic approach of low embedding steganograpy based on high order Histogram moments in frequency domain (HMFD), which provides a key solution to the feature selection and extraction of HMFD. The detection results are tested with the LSB matching steganograpy of different embedding rates in speech signals, respectively, it is proved that the detection performance with HMFD applied is greater than that of histogram statistical moments. HMFD by Wavelet packet decomposition (WPD) can effectively detect low embedding rates Least significant bit (LSB) speech steganography, its accuracy can be 60.8% while the embedding rate is only 3%.