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A Novel Steganalysis of Steghide Focused on High-Frequency Region of Audio Waveform

  • Akira NishimuraEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11378)

Abstract

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.

Keywords

Signal-to-noise ratio Anti-aliasing filter Spectral analysis Information hiding Covert communication 

Notes

Acknowledgment

This work was supported by a Grant-in-Aid for Scientific Research C (JSPS KAKENHI 18K11301), 2018.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Informatics, Faculty of InformaticsTokyo University of Information SciencesWakabaJapan

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