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An Adaptive High Capacity Model for Secure Audio Communication Based on Fractal Coding and Uniform Coefficient Modulation

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Abstract

Securing confidential information over an unsecured communication channel and environment has become an essential aspect. This paper proposes high-capacity audio steganography model based on fractal coding and uniform coefficient modulation, which will be called as HASFC, that simultaneously adjusts the data hiding requirements by increasing the hiding capacity while maintaining the transparency and robustness. HASFC model is based on cover-secret mapping, uniform coefficients modulation and hybrid chaotic map techniques in the transform domain using lifting wavelet. The efficiency of the proposed model is evaluated using a set of experiments, and the audio files are selected from the GTZAN dataset. The empirical findings show improvement in hiding capacity by 30% in comparison with similar techniques in the wavelet domain. Moreover, the transparency is preserved with 50 dB SNR and 4.8 SDG, on average. Furthermore, the proposed model is robust to some signal processing attacks and steganalysis using statistical methods such as the fourth first moment and histogram error ratio. The results signify that the proposed model has notably enhanced the performance of the audio steganography comparing with the related works.

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References

  1. O.I. Abdullaziz, V.T. Goh, H.-C. Ling, K. Wong, AIPISteg: an active IP identification based steganographic method. J. Netw. Comput. Appl. 63, 150–158 (2016)

    Google Scholar 

  2. W.S. Ahmed, L.E. George, Audio hiding using wavelet transform with amplitude modulation. J. Al-Nahrain Univ. 16(1), 183–188 (2013)

    Google Scholar 

  3. A. Al-Haj, An imperceptible and robust audio watermarking algorithm. EURASIP J. Audio Speech Music Process. 2014(1), 37 (2014)

    Google Scholar 

  4. E. Al-Hilo, L.E. George, in Digital Image Computing: Techniques and Applications (DICTA). Speeding-up fractal colored image compression using moments features (2008), pp. 486–490

  5. A.H. Ali, L.E. George, A. Zaidan, M.R. Mokhtar, High capacity, transparent and secure audio steganography model based on fractal coding and chaotic map in temporal domain. Multimed. Tools Appl. 77, 1–30 (2018)

    Google Scholar 

  6. A.H. Ali, M.R. Mokhtar, L.E. George, Recent approaches for VoIP steganography. Indian J. Sci. Technol. 9(38), 6 (2016). https://doi.org/10.17485/ijst/2016/v9i38/101283

    Article  Google Scholar 

  7. A.A. Alsabhany, F. Ridzuan, A. Azni, The adaptive multi-level phase coding method in audio steganography. IEEE Access 7, 129291–129306 (2019)

    Google Scholar 

  8. A. Anees, A.M. Siddiqui, J. Ahmed, I. Hussain, A technique for digital steganography using chaotic maps. Nonlinear Dyn. 75(4), 807–816 (2014)

    Google Scholar 

  9. S. Atawneh, A. Almomani, H. Al Bazar, P. Sumari, B. Gupta, Secure and imperceptible digital image steganographic algorithm based on diamond encoding in DWT domain. Multimed. Tools Appl. 76(18), 1–22 (2016)

    Google Scholar 

  10. D.M. Ballesteros, D. Renza, Secure speech content based on scrambling and adaptive hiding. Symmetry 10(12), 694 (2018)

    Google Scholar 

  11. D.M. Ballesteros, J.M. Moreno, Highly transparent steganography model of speech signals using efficient wavelet masking. Expert Syst. Appl. 39(10), 9141–9149 (2012)

    Google Scholar 

  12. M.F. Barnsley, A.D. Sloan, A better way to compress images. Byte 13(1), 215–223 (1988)

    Google Scholar 

  13. V. Bhat, I. Sengupta, A. Das, An adaptive audio watermarking based on the singular value decomposition in the wavelet domain. Digit. Signal Proc. 20(6), 1547–1558 (2010)

    Google Scholar 

  14. J. Blasco, J.C. Hernandez-Castro, J.M. de Fuentes, B. Ramos, A framework for avoiding steganography usage over HTTP. J. Netw. Comput. Appl. 35(1), 491–501 (2012)

    Google Scholar 

  15. I. Cox, M. Miller, J. Bloom, J. Fridrich, T. Kalker, Digital Watermarking and Steganography (Morgan Kaufmann, Burlington, 2007)

    Google Scholar 

  16. A. Delforouzi, M. Pooyan, Adaptive digital audio steganography based on integer wavelet transform. Circuits Syst. Signal Process. 27(2), 247–259 (2008)

    MathSciNet  Google Scholar 

  17. Ş. Doğan, A new data hiding method based on chaos embedded genetic algorithm for color image. Artif. Intell. Rev. 46(1), 129–143 (2016)

    MathSciNet  Google Scholar 

  18. S.E. El-Khamy, N. Korany, M.H. El-Sherif, in Robust Image Hiding in Audio Based on Integer Wavelet Transform and Chaotic Maps Hopping. 34th National radio science conference (NRSC) (2017), pp. 205–212

  19. S.E. El-Khamy, N.O. Korany, M.H. El-Sherif, A security enhanced robust audio steganography algorithm for image hiding using sample comparison in discrete wavelet transform domain and RSA encryption. Multimed. Tools Appl. 76, 1–16 (2016)

    Google Scholar 

  20. M.B. Farah, A. Farah, T. Farah, An image encryption scheme based on a new hybrid chaotic map and optimized substitution box. Nonlinear Dyn. 8, 1–24 (2019)

    MATH  Google Scholar 

  21. J. Fridrich, Steganography in Digital Media: Principles, Algorithms, and Applications (Cambridge University Press, Cambridge, 2009)

    MATH  Google Scholar 

  22. J.-L. Gailly, M. Nelson, The Data Compression Book (Wiley, New York, 1995)

    Google Scholar 

  23. L.E. George, IFS coding for zero-mean image blocks. Iraqi J. Sci. 47(1), 190–194 (2005)

    Google Scholar 

  24. H. Ghasemzadeh, M.T. Khass, M.K. Arjmandi, Audio steganalysis based on reversed psychoacoustic model of human hearing. Digit. Signal Proc. 51, 133–141 (2016)

    MathSciNet  Google Scholar 

  25. S. Hemalatha, D.U. Acharya, A. Renuka, S. Deepti, J.K. Upadhya, Audio steganography in discrete wavelet transform domain. Int. J. Appl. Eng. Res. 10(16), 36639–36644 (2015)

    Google Scholar 

  26. S. Hemalatha, U.D. Acharya, A. Renuka, Audio data hiding technique using integer wavelet transform. Int. J. Electron. Secur. Digit. Forensics 8(2), 131–147 (2016)

    Google Scholar 

  27. A.E. Jacquin, Image coding based on a fractal theory of iterated contractive image transformations. IEEE Trans. Image Process. 1(1), 18–30 (1992)

    Google Scholar 

  28. A. Kanhe, G. Aghila, A DCT–SVD-based speech steganography in voiced frames. Circuits Syst. Signal Process. 37, 1–20 (2018)

    Google Scholar 

  29. A. Kanhe, G. Aghila, DCT based Audio Steganography in Voiced and Un-voiced Frames, In Proceedings of the International Conference on Informatics and Analytics 2016, p. 47

  30. A. Kanhe, A. Gnanasekaran, A blind audio watermarking scheme employing DCT–HT–SD technique. Circuits Syst. Signal Process. 38(8), 3697–3714 (2019)

    Google Scholar 

  31. D.C. Kar, C.J. Mulkey, A multi-threshold based audio steganography scheme. J. Inf. Secur. Appl. 23, 54–67 (2015)

    Google Scholar 

  32. A. Kaur, M.K. Dutta, K. Soni, N. Taneja, Localized and self adaptive audio watermarking algorithm in the wavelet domain. J. Inf. Secur. Appl. 33, 1–15 (2017)

    Google Scholar 

  33. M.F. Khan, F. Baig, S. Beg, Steganography between silence intervals of audio in video content using chaotic maps. Circuits Syst. Signal Process. 33(12), 3901–3919 (2014)

    Google Scholar 

  34. B. Lei, Y. Soon, A multipurpose audio watermarking algorithm with synchronization and encryption. J. Zhejiang Univ. Sci. C 13(1), 11–19 (2012)

    Google Scholar 

  35. B. Lei, Y. Soon, F. Zhou, Z. Li, H. Lei, A robust audio watermarking scheme based on lifting wavelet transform and singular value decomposition. Signal Process. 92(9), 1985–2001 (2012)

    Google Scholar 

  36. M. Mosleh, H. Latifpour, M. Kheyrandish, M. Mosleh, N. Hosseinpour, A robust intelligent audio watermarking scheme using support vector machine. Front. Inf. Technol. Electron. Eng. 17(12), 1320–1330 (2016)

    Google Scholar 

  37. M. Pooyan, A. Delforouzi, in LSB-Based Audio Steganography Method Based on Lifting Wavelet Transform. IEEE international symposium on signal processing and information technology (2007), pp. 600–603

  38. D. Renza, C. Lemus, Authenticity verification of audio signals based on fragile watermarking for audio forensics. Expert Syst. Appl. 91, 211–222 (2018)

    Google Scholar 

  39. D. Renza, C. Lemus, D.M. Ballesteros, in Highly Transparent and Secure Scheme for Concealing Text Within Audio. Iberoamerican congress on pattern recognition (2017), pp. 27–35

  40. E. Rivas, Fourier phase domain steganography: phase bin encoding via interpolation. Paper presented at the mobile multimedia/image processing for military and security applications (2007)

  41. D. Salomon, G. Motta, Handbook of Data Compression (Springer, New York, 2010)

    MATH  Google Scholar 

  42. H.I. Shahadi, R. Jidin, in High Capacity and Inaudibility Audio Steganography Scheme. 7th International conference on information assurance and security (IAS) (2011), pp. 104–109

  43. H.I. Shahadi, R. Jidin, W.H. Way, A novel and high capacity audio steganography algorithm based on adaptive data embedding positions. Res. J. Appl. Sci. Eng. Technol. 7(11), 2311–2323 (2014)

    Google Scholar 

  44. H.I. Shahadi, R. Jidin, W.H. Way, Concurrent hardware architecture for dual-mode audio steganography processor-based FPGA. Comput. Electr. Eng. 49, 95–116 (2016)

    Google Scholar 

  45. H.I. Shahadi, R. Jidin, W.H. Way, Lossless audio steganography based on lifting wavelet transform and dynamic Stego Key. Indian J. Sci. Technol. 7(3), 323–334 (2014)

    Google Scholar 

  46. M. Sheikhan, K. Asadollahi, R. Shahnazi, Improvement of embedding capacity and quality of DWT-based audio steganography systems. World Appl. Sci. J. 13(3), 507–516 (2011)

    Google Scholar 

  47. S. Shirali-Shahreza, M.T. Manzuri-Shalmani, in Adaptive Wavelet Domain Audio Steganography with High Capacity and Low Error Rate. International conference on information and emerging technologies (2007), pp. 1–5

  48. M. Tang, S. Zeng, X. Chen, J. Hu, Y. Du, An adaptive image steganography using AMBTC compression and interpolation technique. Opt. Int. J. Light Electron Opt. 127(1), 471–477 (2016). https://doi.org/10.1016/j.ijleo.2015.09.216

    Article  Google Scholar 

  49. C.S. Tong, M. Pi, Fast fractal image encoding based on adaptive search. IEEE Trans. Image Process. 10(9), 1269–1277 (2001). https://doi.org/10.1109/83.941851

    Article  Google Scholar 

  50. A.Y. Tuama, M.A. Mohamed, A. Muhammed, Z.M. Hanapi, Randomized pixel selection for enhancing LSB algorithm security against brute-force attack. J. Math. Stat. 12, 127–138 (2017)

    Google Scholar 

  51. G. Tzanetakis, Music Analysis, Retrieval and Synthesis for Audio Signals (Marsyas) (2009). http://marsyasweb.appspot.com/download/data_sets/. Accessed 22 Nov 2015

  52. S.S. Verma, R. Gupta, G. Shrivastava, in A Novel Technique for Data Hiding in Audio Carrier by Using Sample Comparison in DWT Domain. Fourth international conference on communication systems and network technologies (CSNT) (2014), pp. 639–643

  53. B. Zaidan, A. Zaidan, H.A. Karim, N. Ahmad, A new digital watermarking evaluation and benchmarking methodology using an external group of evaluators and multi-criteria analysis based on ‘large-scale data’. Softw. Pract. Exp. 47, 1365–1392 (2016)

    Google Scholar 

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Acknowledgement

This research is supported by the Ministry of Higher Education and Scientific Research, Studies Planning and Follow-up Directorate, Iraq and the Research Centre for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia UKM, Malaysia.

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Authors and Affiliations

  1. Ministry of Higher Education and Scientific Research, Studies Planning and Follow-up Directorate, Baghdad, Iraq

    Ahmed Hussain Ali

  2. University of Information Technology and Communication UoITC, Baghdad, Iraq

    Loay Edwar George

  3. Centre for Cyber Security, Universiti Kebangsaan Malaysia UKM, Bangi, Malaysia

    Ahmed Hussain Ali & Mohd Rosmadi Mokhtar

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  1. Ahmed Hussain Ali
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Ali, A.H., George, L.E. & Mokhtar, M.R. An Adaptive High Capacity Model for Secure Audio Communication Based on Fractal Coding and Uniform Coefficient Modulation. Circuits Syst Signal Process 39, 5198–5225 (2020). https://doi.org/10.1007/s00034-020-01409-7

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