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BCH encoded robust and blind audio watermarking with tamper detection using hash

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Abstract

International Federation of Phonographic Industry (IFPI) has laid requirements for digital audio watermarking (DAW) schemes with regard to robustness, imperceptibility and payload. In addition, DAW schemes have to offer audio integrity. Many of the schemes fails to provide both copyright protection and tamper detection. Moreover, tamper detection of audio is not evaluated in quantitative manner. Therefore, a robust and blind DAW scheme has been developed in transform domain to suffice this requirement. Further, an objective performance metric, detection accuracy, is proposed to quantify the performance of tamper detection. In the proposed work, audio is fragmented and transform coefficients are obtained using Wavelet and Cosine Transforms. Watermark image is pre-processed using logistic map and BCH code. This pre-processed image is inserted into singular values of audio signal coefficients through quantization index modulation. Hash is generated with SHA-512 algorithm and is inserted in watermarked audio frames. Hash recovery at the receiver allows to identify any tampering involved in audio viz., deletion, copy-move and substitute attacks. Singular vectors are not required to extract the watermark, thus this method is free from false positive problem and can provide copyright protection. Experimentation is carried out on five different classes of audios which substantiates that robustness, imperceptibility and payload results are acquiescent to IFPI standard. Further, comparative analysis indicates that developed scheme is better when compared with other state-of art-schemes. Consequently, this DAW scheme helps in forensic examination of audio recording for authentication purpose.

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References

  1. Ahmad M, Al Solami E, Wang XY, Doja MN, Sufyan Beg MM, Alzaidi AA (2018) Cryptanalysis of an image encryption algorithm based on combined chaos for a BAN system, and improved scheme using SHA-512 and hyperchaos. Symmetry 10(7):1–18

    Article  Google Scholar 

  2. Al-Haj A (2014) A dual transform audio watermarking algorithm. Multimed Tools Appl 73(3):1897–1912

    Article  Google Scholar 

  3. Chen X, Yuan W, Wang S, Wang C, Wang L (2019) Speech Watermarking for Tampering Detection Based on Modifications to LSFs. Mathematical Problems in Engineering 1–10

  4. Cichowski J, Czyżewski A, Kostek B (2015) Analysis of impact of audio modifications on the robustness of watermark for non-blind architecture. Multimed Tools Appl 74(12):4415–4435

    Article  Google Scholar 

  5. Erçelebi E, Batakçı L (2009) Audio watermarking scheme based on embedding strategy in low frequency components with a binary image. Digit Signal Process 19(2):265–277

    Article  Google Scholar 

  6. Guo J, Riyono D, Prasetyo H (2019) Hyperchaos permutation on false-positive-free SVD-based image watermarking. Multimed Tools Appl 78:29229–29270

    Article  Google Scholar 

  7. Hu H, Chang J (2017) Efficient and robust frame-synchronized blind audio watermarking by featuring multilevel DWT and DCT. Clust Comput 20(1):805–816

    Article  Google Scholar 

  8. Hu HT, Hsu LY (2015) Robust, transparent and high-capacity audio watermarking in DCT domain. Signal Process 109:226–235

    Article  Google Scholar 

  9. Hu HT, Hsu LY (2016) A DWT-based rational dither modulation scheme for effective blind audio watermarking. Circuits Syst Signal Process 35(2):553–572

    Article  Google Scholar 

  10. Hu HT, Hsu LY, Chou HH (2014) Variable-dimensional vector modulation for perceptual-based DWT blind audio watermarking with adjustable payload capacity. Digit Signal Process 31:115–123

    Article  Google Scholar 

  11. Hu HT, Lee TT (2019) Hybrid blind audio watermarking for proprietary protection, tamper proofing, and self-recovery. IEEE Access 7:180395–180408

    Article  Google Scholar 

  12. Hu HT, Lin SJ, Hsu LY (2017) Effective blind speech watermarking via adaptive mean modulation and package synchronization in DWT domain. Eurasip J Audio Speech Music Process 1:1–14

    Google Scholar 

  13. Jo D, Kwon S, Shin DJ (2018) Blind reconstruction of BCH codes based on consecutive roots of generator polynomials. IEEE Commun Lett 22(5):894–897

    Article  Google Scholar 

  14. Karajeh H, Maqableh M (2019) An imperceptible, robust, and high payload capacity audio watermarking scheme based on the DCT transformation and Schur decomposition. Analog Integr Circuits Signal Process 99:571–583

    Article  Google Scholar 

  15. Kaur A, Dutta MK (2018) An optimized high payload audio watermarking algorithm based on LU-factorization. Multimed Syst 24(3):341–353

    Article  Google Scholar 

  16. Kaur A, Dutta MK (2018) High embedding capacity and robust audio watermarking for secure transmission using tamper detection. ETRI J40(1):133–145

    Article  Google Scholar 

  17. Lalitha NV, Rao CS, JayaSree PVY (2016) Robust audio watermarking scheme with synchronization code and QIM. Int J Eng Technol 8(1):486–500

    Google Scholar 

  18. Lalitha N, Rao S, JayaSree P (2013) DWT — Arnold Transform based audio watermarking. 2013 IEEE Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia), pp 196–199

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

    Article  Google Scholar 

  20. Lie WN, Chang LC (2006) Robust and high-quality time-domain audio watermarking based on low-frequency amplitude modification. IEEE Trans Multimed 8(1):46–59

    Article  Google Scholar 

  21. Makbol NM, Khoo BE, Rassem TH (2018) Security analyses of false positive problem for the SVD-based hybrid digital image watermarking techniques in the wavelet transform domain. Multimed Tools Appl 77:26845–26879

    Article  Google Scholar 

  22. Meenakshi K, Swaraja K, Kora P (2020) A hybrid matrix factorization technique to free the watermarking scheme from false positive and negative problems. Multimed Tools Appl 79:29865–29900

    Article  Google Scholar 

  23. Mehallegue N, Loukhaoukha K, Zebbiche K, Refaey A, Djellab M (2020) Ambiguity attacks on SVD audio watermarking approach using chaotic encrypted images. Multimed Tools Applic 79(3–4):2031–2045

    Article  Google Scholar 

  24. Homburg, H, Mierswa I, Moller B, Morik K, Wurst M (2005) A Benchmark Dataset for Audio Classification and Clustering In: Reiss JD, Wiggins GA (eds) Proc. of the International Symposium on Music Information Retrieval 2005, London, UK, Queen Mary University, pp 528–531

  25. Pourhashemi SM, Mosleh M, Erfani Y (2019) Audio watermarking based on synergy between Lucas regular sequence and Fast Fourier Transform. Multimed Tools Appl 78(16):22883–22908

    Article  Google Scholar 

  26. Shi C, Li X, Wang H (2020) A novel integrity authentication algorithm based on perceptual speech hash and learned dictionaries. IEEE Access 8:22249–22265

    Article  Google Scholar 

  27. Wang X, Wang P, Zhang P, Xu S, Yang H (2014) A blind audio watermarking algorithm by logarithmic quantization index modulation. Multimed Tools Applic 71(3):1157–1177

    Article  Google Scholar 

  28. Wu Q, Wu M (2018) A novel robust audio watermarking algorithm by modifying the average amplitude in transform domain. Appl Sci 8(723):1–17

    Google Scholar 

  29. Xiang S, Yang L, Wang Y (2017) Robust and reversible audio watermarking by modifying statistical features in time domain. Advances in Multimedia, Article ID 8492672:1–10

  30. Zhu S, Zhu C, Wang W (2018) A new image encryption algorithm based on chaos and secure hash SHA-256. Entropy 20(9):716

    Article  Google Scholar 

Download references

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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Authors and Affiliations

  1. Department of Electronics & Communication Engineering, GMR Institute of Technology, Rajam, A.P, India

    Venkata Lalitha Narla & Suresh Gulivindala

  2. Department of Electronics & Communication Engineering, JNTUK University College of Engineering, Vizianagaram, A.P, India

    Srinivasa Rao Chanamallu

  3. Central Forensic Science Laboratory, Chandigarh, Punjab, India

    D P Gangwar

Authors
  1. Venkata Lalitha Narla
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  2. Suresh Gulivindala
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  3. Srinivasa Rao Chanamallu
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  4. D P Gangwar
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Correspondence to Venkata Lalitha Narla.

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Narla, V.L., Gulivindala, S., Chanamallu, S.R. et al. BCH encoded robust and blind audio watermarking with tamper detection using hash. Multimed Tools Appl 80, 32925–32945 (2021). https://doi.org/10.1007/s11042-021-11370-5

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  • DOI: https://doi.org/10.1007/s11042-021-11370-5

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