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Circuits, Systems, and Signal Processing

, Volume 33, Issue 11, pp 3475–3498 | Cite as

Speech Scrambling Based on Imitation of a Target Speech Signal with Non-confidential Content

Article

Abstract

This paper shows a new approach of speech scrambling using imitation to produce a scrambled speech signal with intelligible content. The secret message imitates a target speech signal with non-confidential content through an adaptation mechanism. Unlike the classical approach, the key is not an input of the system because it is created in the adaptation process. Several tests are conducted in order to validate adaptation as an efficient key generator, and the robustness of the scrambled speech signal against signal manipulation attacks. The advantages of our proposal are (1) the scrambled speech signal is an intelligible speech signal so that it does not generate suspicious about the existence of the secret message, (2) the system does not require an external key generator because the elements are permutated according to the adaptation process, (3) the length of the key is long enough so that it guarantees that the key is not found by brute-force attack, and (4) it works with perfect secrecy because the a priori probability of the secret message is the same as the a posteriori probability, given the scrambled speech signal.

Keywords

Speech security Scrambling Adaptation Residual intelligibility Perfect secrecy Robustness 

References

  1. 1.
    S.M.H. Alwahbani, E.B.M. Bashier, in Speech scrambling based on chaotic maps and one time pad. Proceedings of International Conference on Computing, Electrical and Electronics Engineering (2013), pp. 128–133Google Scholar
  2. 2.
    R.J. Anderson, F.A.P. Petitcolas, On the limits of steganography. IEEE J. Sel. Areas Commun. 16, 474–481 (1998)CrossRefGoogle Scholar
  3. 3.
    D.M. Ballesteros L, J.M. Moreno A, Highly transparent steganography model of speech signals using Efficient Wavelet Masking. Expert Syst. Appl. 39, 9141–9149 (2012)CrossRefGoogle Scholar
  4. 4.
    D.M. Ballesteros L, J.M. Moreno A, On the ability of adaptation of speech signals and data hiding. Expert Syst. Appl. 39, 12574–12579 (2012)CrossRefGoogle Scholar
  5. 5.
    D.M. Ballesteros L, J.M. Moreno A, A bit more on the ability of adaptation of speech signals. Rev. Fac. Ing. Univ. Antioq. 66, 82–90 (2013)Google Scholar
  6. 6.
    D.M. Ballesteros L, J.M. Moreno A, Real-time, speech-in-speech hiding scheme based on least significant bit substitution and adaptive key. Comput. Electr. Eng. 39, 1192–1203 (2013)CrossRefGoogle Scholar
  7. 7.
    J. Benesty, J. Chen, Y. Huang, I. Cohen, Pearson Correlation Coefficient, Noise Reduction in Speech Processing (Springer, Berlin, 2009)Google Scholar
  8. 8.
    J. Benesty, C. Jingdong, H. Yiteng, On the importance of the pearson correlation coefficient in noise reduction. IEEE Trans. Audio Speech Lang. Process. 16, 757–765 (2008)Google Scholar
  9. 9.
    J.F. de Andrade, M.L.R. De Campos, J.A. Apolinario, in Speech Privacy for Modern Mobile Communication Systems. Proceedings of IEEE international conference on acoustics, speech and signal processing, ICASSP, (2008), pp. 1777–1780Google Scholar
  10. 10.
    E. Del Re, R. Fantacci, D. Maffucci, A new speech signal scrambling method for secure communications: theory, implementation, and security evaluation. IEEE J. Sel. Areas Commun. 7, 474–480 (1989)CrossRefGoogle Scholar
  11. 11.
    F. Djebbar, B. Ayad, K. Meraim, H. Hamam, Comparative study of digital audio steganography techniques. Eurasip J. Audio Speech Music Process. 2012, 1–16 (2012)Google Scholar
  12. 12.
    R.C. French, Speech scrambling. Electron. Power 18, 263–264 (1972)CrossRefGoogle Scholar
  13. 13.
    M. Fulong, C. Jun, W. Yumin, Wavelet transform-based analogue speech scrambling scheme. Electron. Lett. 32, 719–721 (1996)CrossRefGoogle Scholar
  14. 14.
    B. Goldburg, S. Sridharan, E. Dawson, Cryptanalysis of frequency domain analogue speech scramblers. IEE Proc. I Commun. Speech Vis. 140, 235–239 (1993)CrossRefGoogle Scholar
  15. 15.
    B. Goldburg, S. Sridharan, E. Dawson, Design and cryptanalysis of transform-based analog speech scramblers. IEEE J. Sel. Areas Commun. 11, 735–744 (1993)CrossRefGoogle Scholar
  16. 16.
    A. Jameel, M.Y. Siyal, N. Ahmed, Transform-domain and DSP based secure speech communication system. Microprocess. Microsyst. 31, 335–346 (2007)CrossRefGoogle Scholar
  17. 17.
    N.S. Jayant, Analog scramblers for speech privacy. Comput. Secur. 1, 275–289 (1982)CrossRefGoogle Scholar
  18. 18.
    S.C. Kak, Encryption of signals using data transpositions. Proc. Inst. Electr. Eng. 125, 1327–1328 (1978)CrossRefGoogle Scholar
  19. 19.
    H. Li, Z. Qin, L. Shao, S. Zhang, B. Wang, Variable Dimension Space Audio Scrambling Algorithm Against MP3 Compression, in Algorithms and Architectures for Parallel Processing, ed. by A. Hua, S.-L. Chang (Springer, Berlin, 2009), pp. 866–876CrossRefGoogle Scholar
  20. 20.
    Y.C. Lim, J.W. Lee, S.W. Foo, Quality analog scramblers using frequency-response masking filter banks. Circuits Syst. Signal Process. 29, 135–154 (2010)CrossRefMATHGoogle Scholar
  21. 21.
    A. Madain, A. Abu, Dalhoum, H. Hiary, A. Ortega, M. Alfonseca, Audio scrambling technique based on cellular automata. Multimed. Tools Appl. (2012). doi: 10.1007/s11042-012-1306-7
  22. 22.
    A. Matsunaga, K. Koga, M. Ohkawa, An analog speech scrambling system using the FFT technique with high-level security. IEEE J. Sel. Areas Commun. 7, 540–547 (1989)CrossRefGoogle Scholar
  23. 23.
    E. Mosa, N.W. Messiha, O. Zahran, in Random Encryption of Speech Signal. Proceedings of international conference on computer engineering & systems, ICCES, (2009), pp. 306–311Google Scholar
  24. 24.
    M.A. Pathak, B. Raj, Privacy-preserving speaker verification and identification using Gaussian mixture models. IEEE Trans. Audio Speech Lang. Process. 21, 397–406 (2013)CrossRefGoogle Scholar
  25. 25.
    M.A. Pathak, B. Raj, S.D. Rane, P. Smaragdis, Privacy-preserving speech processing: cryptographic and string-matching frameworks show promise. IEEE Signal Process. Mag. 30, 62–74 (2013)CrossRefGoogle Scholar
  26. 26.
    V.J. Phillips, M.H. Lee, J.E. Thomas, Speech scrambling by the re-ordering of amplitude samples. Radio Electr. Eng. 41, 99 (1971)CrossRefGoogle Scholar
  27. 27.
    S.B. Sadkhan, N. Abdulmuhsen, N.F. Al-Tahan, in A Proposed Analog Speech Scrambler Based on Parallel Structure of Wavelet Transforms. Proceedings of national radio science conference, NRSC (2007), pp. 1–12Google Scholar
  28. 28.
    C.E. Shannon, Communication theory of secrecy systems. Bell Syst. Tech. J. 28, 656–715 (1949)MathSciNetCrossRefMATHGoogle Scholar
  29. 29.
    G. Simmons, The prisoners’ problem and the subliminal channel, in Advances in Cryptology, ed. by D. Chaum (Springer, US, 1984), pp. 51–67CrossRefGoogle Scholar
  30. 30.
    SLT, Class-Talk: A University teaching phrasebook., Universitat Politecnica de Catalunya. http://www.upc.edu/slt/classtalk/a.php?idioma%5B%5D=1&idioma%5B%5D=7&tematica=2&fer=guianova
  31. 31.
    B.K. Sy, in Slice-based Architecture for Biometrics: Prototype Illustration on Privacy Preserving Voice Verification. Proceedings of IEEE 3rd international conference on biometrics: theory, applications, and systems, BTAS (2009), pp. 1–6Google Scholar
  32. 32.
    D.C. Tseng, J.H. Chiu, in An OFDM Speech Scrambler Without Residual Intelligibility. Proceedings of IEEE region 10 conference TENCON (2007), pp. 1–4Google Scholar
  33. 33.
    R.W. Woo, C. Leung, A new key generation method for frequency-domain speech scramblers. IEEE Trans. Commun. 45, 749–752 (1997)CrossRefMATHGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Telecommunications EngineeringUniversidad Militar Nueva GranadaBogotáColombia
  2. 2.Department of Electronic EngineeringUniversitat Politecnica de CatalunyaBarcelonaSpain

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