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International Workshop on Digital Watermarking

IWDW 2017: Digital Forensics and Watermarking pp 177–186Cite as

Adaptive Audio Steganography Based on Advanced Audio Coding and Syndrome-Trellis Coding

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 10431))

Abstract

Most existing audio steganographic methods embed secret messages according to a pseudorandom number generator, thus some auditory sensitive parts in cover audio, such as mute or near-mute segments, will be contaminated, which would lead to poor perceptual quality and may introduce some detectable artifacts for steganalysis. In this paper, we propose a novel adaptive audio steganography in the time domain based on the advanced audio coding (AAC) and the Syndrome-Trellis coding (STC). The proposed method firstly compresses a given wave signal into AAC compressed file with a high bitrate, and then obtains a residual signal by comparing the signal before and after AAC compression. According to the quantity and sign of the residual signal, \(\pm 1\) embedding costs are assigned to the audio samples. Finally, the STC is used to create the stego audio. The extensive results evaluated on 10,000 music and 10,000 speech audio clips have shown that our method can significantly outperform the conventional \(\pm 1\) LSB based steganography in terms of security and audio quality.

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Notes

  1. 1.

    The STC tool is available at: http://dde.binghamton.edu/download/syndrome.

  2. 2.

    Nero AAC Codec is available at: http://nero-aac-codec.en.lo4d.com.

References

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Acknowledgments

This work is supported in part by the NSFC (61672551), the Fok Ying-Tong Education Foundation (142003), the special research plan of Guangdong Province (2015TQ01X365), and the Guangzhou science and technology project (201707010167)

Author information

Authors and Affiliations

  1. Guangdong Key Laboratory of Information Security and Technology, Guangzhou, People’s Republic of China

    Weiqi Luo, Yue Zhang & Haodong Li

  2. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, People’s Republic of China

    Weiqi Luo, Yue Zhang & Haodong Li

Authors
  1. Weiqi Luo
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  2. Yue Zhang
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  3. Haodong Li
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Corresponding author

Correspondence to Weiqi Luo .

Editor information

Editors and Affiliations

  1. Department of Computer Science, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    Christian Kraetzer

  2. Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, New Jersey, USA

    Yun-Qing Shi

  3. Department of Computer Science, Otto-von-Guericke University Magdeburg, Magdeburg, Germany

    Jana Dittmann

  4. Graduate School Information Security, Korea University, Seoul, Korea (Republic of)

    Hyoung Joong Kim

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Luo, W., Zhang, Y., Li, H. (2017). Adaptive Audio Steganography Based on Advanced Audio Coding and Syndrome-Trellis Coding. In: Kraetzer, C., Shi, YQ., Dittmann, J., Kim, H. (eds) Digital Forensics and Watermarking. IWDW 2017. Lecture Notes in Computer Science(), vol 10431. Springer, Cham. https://doi.org/10.1007/978-3-319-64185-0_14

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  • DOI: https://doi.org/10.1007/978-3-319-64185-0_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64184-3

  • Online ISBN: 978-3-319-64185-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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