Skip to main content
Log in

64-bit quantization: taking payload capacity of speech steganography to the limits

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

A fundamental problem in steganography is the trade-off between the hiding capacity and the quality of the stego signal. Researchers have found in the Discrete Cosine Transform (DCT) a potential solution to this trade-off challenge due to its strong compaction property. The DCT has the ability to represent a time-domain signal within a few numbers of DCT coefficients leaving a substantial amount of insignificant DCT coefficients that can host the secret data. Moreover, it has been found that the compaction property becomes stronger with highly-correlated signals. Therefore, this paper suggests to fully exploit the strong compaction property of the DCT by segmenting the cover speech signal into correlated segments. Hiding is performed in the insignificant DCT coefficients in each segment which are determined by a new quantization method suitable for speech signals. Experimental results have proven that the proposed steganography technique has outperformed competing speech hiding schemes, in terms of the payload capacity which reached up to 14.94 bps, at similar or higher stego quality.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Notes

  1. https://www.globenewswire.com/news-release/2019/04/23/1807634/0/en/Voice-over-Internet-Protocol-VoIP-Market-to-hit-55bn-by-2025-Global-Market-Insights-Inc.htmlhttps://www.globenewswire.com/news-release/2019/04/23/1807634/0/en/Voice-over-Internet-Protocol-VoIP-Market-to-hit-55bn-by-2025-Global-Market-Insights-Inc.html

  2. https://speech-to-text-demo.ng.bluemix.net/

References

  1. Ahmed MA, Kiah MLM, Zaidan B, Zaidan A (2010) A novel embedding method to increase capacity and robustness of low-bit encoding audio steganography technique using noise gate software logic algorithm. J Appl Sci 10(1):59–64

    Article  Google Scholar 

  2. Ahmed N, Natarajan T, Rao KR (1974) Discrete cosine transform. IEEE transactions on Computers 100(1):90–93

    Article  MathSciNet  Google Scholar 

  3. Anushiadevi R, Praveenkumar P, Rayappan JBB, Amirtharajan R (2021) Uncover the cover to recover the hidden secret-a separable reversible data hiding framework. Multimed Tools Appl, 1–20

  4. Ballesteros DML, Moreno JMA (2012) Highly transparent steganography model of speech signals using efficient wavelet masking. Expert Syst Appl 39 (10):9141–9149

    Article  Google Scholar 

  5. Baziyad M, Obaidat MS (2020) On the importance of the dct phase for image steganography schemes. In: 2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA). IEEE, pp 791–795

  6. Baziyad M, Rabie T (2020) I Kamel, A new high capacity video steganography scheme using differential directional pixogram. In: 2020 14th international conference on innovations in information technology (IIT). IEEE, pp 40–44

  7. Baziyad M, Rabie T, Kamel I (2018) Extending steganography payload capacity using the l* a* b* color space. In: 2018 international conference on innovations in information technology (IIT), pp 1–6

  8. Baziyad M, Rabie T, Kamel I (2020) Achieving stronger compaction for dct-based steganography: a region-growing approach. In: World Conference on Information Systems and Technologies. Springer, Cham, pp 251–261

  9. Baziyad M, Rabie T, Kamel I (2020) Toward stronger energy compaction for high capacity dct-based steganography: a region-growing approach. Multimed Tools Appl 80(6):1–27

    Google Scholar 

  10. Erfani Y, Siahpoush S (2009) Robust audio watermarking using improved ts echo hiding. Digital Signal Processing 19(5):809–814

    Article  Google Scholar 

  11. Ghasemzadeh H, Arjmandi MK (2017) Universal audio steganalysis based on calibration and reversed frequency resolution of human auditory system. IET Signal Processing 11(8):916–922

    Article  Google Scholar 

  12. Kathum AM, Al-Saad SN (2016) Speech steganography system using lifting wavelet transform, vol 19

  13. Katz J, Lindell Y (2014) Introduction to modern cryptography. Chapman and hall/CRC, London

    Book  Google Scholar 

  14. Kitawaki N, Honda M, Itoh K (1984) Speech-quality assessment methods for speech-coding systems. IEEE Commun Mag 22(10):26–33

    Article  Google Scholar 

  15. Korzhik VI, Morales-Luna G, Fedyanin I (2013) Audio watermarking based on echo hiding with zero error probability. IJCSA 10(1):1–10

    Google Scholar 

  16. Lakshmi C, Ravi VM, Thenmozhi K, Rayappan JBB, Amirtharajan R (2020) Con (dif) fused voice to convey secret: a dual-domain approach. Multimedia Systems, 1–11

  17. Lee MC, Lau CY (2018) Three orders mixture algorithm of audio steganography combining cryptography. J Inf Hiding Multimed Signal Process 9, 4

  18. Liu H, Liu J, Yan X, Xue P, Wan S, Li L (2018) Centroid-based audio steganography scheme in wavelet domain. J Info Hiding Multimed Signal Process 9(5):1222–1232

    Google Scholar 

  19. Liu J, Zhou K, Tian H (2012) Least-significant-digit steganography in low bitrate speech. In: 2012 IEEE international conference on communications (ICC). IEEE, pp 1133–1137

  20. Muñoz A (2015) Stegsecret a simple steganalysis tool. stegsecret. sourceforge. net

  21. Nassif AB, Shahin I, Attili I, Azzeh M, Shaalan K (2019) Speech recognition using deep neural networks: a systematic review. IEEE Access 7:19143–19165

    Article  Google Scholar 

  22. Nassrullah HA, Flayyih WN, Nasrullah MA (2020) Enhancement of lsb audio steganography based on carrier and message characteristics. J Info Hiding Multimed Signal Process 11(3):126–137

    Google Scholar 

  23. Oppenheim AV, Lim JS (1981) The importance of phase in signals. Proc IEEE 69(5):529–541

    Article  Google Scholar 

  24. Rabie T, Baziyad M, Kamel I (2018) Enhanced high capacity image steganography using discrete wavelet transform and the laplacian pyramid. Multimed Tools Appl, 1–26

  25. Rabie T, Guerchi D (2015) Spectral magnitude speech steganography. Int J Comput Appl Technol 116(5)

  26. Rabie T, Kamel I (2017) Toward optimal embedding capacity for transform domain steganography: a quad-tree adaptive-region approach. Multimed Tools Appl 76(6):8627–8650

    Article  Google Scholar 

  27. Rabie T, Kamel I, Baziyad M (2018) Maximizing embedding capacity and stego quality: curve-fitting in the transform domain. Multimed Tools Appl 77(7):8295–8326

    Article  Google Scholar 

  28. Rachael O, Misra S, Ahuja R, Adewumi A, Ayeni F, Mmaskeliunas R (2020) Image steganography and steganalysis based on least significant bit (lsb). In: Proceedings of ICETIT 2019. Springer, pp 1100–1111

  29. Saiz-Alía M, Forte AE, Reichenbach T (2019) Individual differences in the attentional modulation of the human auditory brainstem response to speech inform on speech-in-noise deficits. Scientific Reports 9(1):1–10

    Article  Google Scholar 

  30. Saračević M, Adamović S, Miškovic V, Maček N, Šarac M (2019) A novel approach to steganography based on the properties of catalan numbers and dyck words. Futur Gener Comput Syst 100:186–197

    Article  Google Scholar 

  31. Shahin IMA (2013) Employing both gender and emotion cues to enhance speaker identification performance in emotional talking environments. International Journal of Speech Technology 16(3):341–351

    Article  Google Scholar 

  32. Shirali-Shahreza S, Manzuri-Shalmani M (2008) High capacity error free wavelet domain speech steganography. In: 2008 IEEE international conference on acoustics, speech and signal processing. IEEE, pp 1729–1732

  33. Shrestha S, Wahid K (2010) Hybrid dwt-dct algorithm for biomedical image and video compression applications. In: 2010 10th international conference on information sciences signal processing and their applications (ISSPA). IEEE, pp 280–283

  34. Sridevi R, Damodaram A, Narasimham S (2009) Efficient method of audio steganography by modified lsb algorithm and strong encryption key with enhanced security. Journal of Theoretical & Applied Information Technology 5:6

    Google Scholar 

  35. Sweldens W (1998) The lifting scheme: a construction of second generation wavelets. SIAM J Math Anal 29(2):511–546

    Article  MathSciNet  Google Scholar 

  36. White R, Banks E (2017) Computer networking problems and solutions: an innovative approach to building resilient, modern networks Addison-Wesley Professional

  37. Xu T, Yang Z (2009) Simple and effective speech steganography in g. 723.1 low-rate codes. In: 2009 international conference on wireless communications & signal processing. IEEE, pp 1–4

  38. Xu T, Yang Z, Shao X (2009) Novelspeech secure communication system based on information hiding and compressed sensing. In: 2009 fourth international conference on systems and networks communications. IEEE, pp 201–206

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohammed Baziyad.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Baziyad, M., Shahin, I., Rabie, T. et al. 64-bit quantization: taking payload capacity of speech steganography to the limits. Multimed Tools Appl 81, 40561–40579 (2022). https://doi.org/10.1007/s11042-022-13138-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-022-13138-x

Keywords