A novel steganalysis of Steghide focused on high-frequency region of audio waveform
A novel steganalysis of Steghide focused on high-frequency region of audio waveform
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一种针对音频波形高频区域的新型 Steghide 隐写分析
DOI：
10.1007/978-3-030-11389-6_6
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Akira Nishimura
中科院分区：
文献类型：
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作者：
小林 栄介;酒澤 茂之;Akira Nishimura
本文研究了微软RIFF波形音频格式(WAV)数据中隐藏信息的隐写分析。频谱分析表明，传统的隐写分析有意无意地利用了目标信号的高频区域和静默时间段的统计信息。此外，仅低于奈奎斯特频率的频率分量对于基于统计的隐写分析来说是重要的，其中信号对应于数据隐藏引起的失真分量，而噪声对应于掩蔽信号。提出了一种充分利用高频特征的隐写分析方法，并将其检测性能与传统方法进行了比较，结果表明该方法具有较好的检测性能。结果表明，对于100个音乐信号和320个混杂背景噪声的语音信号，本文提出的隐写分析方法优于传统的隐写方法。
In this study, steganalysis of steghide embedded in Microsoft RIFF waveform audio format (WAV) data is investigated. Spectral analyses show that the conventional steganalysis utilize the statistics of high-frequency regions and silent temporal segments of the target signals intentionally or unintentionally. Moreover, the frequency components just below the Nyquist frequency are important for statistic-based steganalysis in terms of the signal-to-noise ratio where the signal corresponds to the distortion components induced by data hiding, and the noise corresponds to the cover signal. A novel steganalysis making full use of the high- frequency features is proposed, and its detection performance is compared with the conventional method, which showed the best performance so far. The results show that the proposed steganalysis outperforms the conventional method for cover data of 100 music signals and 320 speech signals mixed with background noises.