Abstract
To solve the copyright problem of audio data, many singular value decomposition (SVD)-based audio watermarking schemes have been proposed, however, most SVD-based schemes cannot improve the imperceptibility and robustness while guaranteeing a certain embedding capacity. Therefore, we propose a new SVD-based adaptive robust audio watermarking method. In this method, after framing the host audio signal, a discrete wavelet transform (DWT) is performed on each frame, and then the obtained DWT coefficients are divided into two segments using a sub-sampling operation, and the SVD is performed on these two segments and the mean value of the two singular values is calculated. Then the watermark bits are embedded by modifying the singular values of the two segments using differential embedding method. In the above watermark embedding process, the proposed adaptive method generates different sizes of embedding parameters according to the original signal features of each frame to minimize the degradation of perceived quality. During the watermark extraction process, the watermark can still be correctly extracted without the original audio signal and embedding parameters. The experimental results show that the scheme is more robust than existing audio watermarking schemes under various attacks with a certain embedding capacity guaranteed.






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References
Wang Y, Pan Y, Yan M, Su Z, Luan TH (2023) A survey on ChatGPT: AI-generated contents, challenges, and solutions
Hu R, Xiang S (2021) Lossless robust image watermarking by using polar harmonic transform. Signal Process 179:107833
Chen Y, Jia Z-G, Peng Y, Peng Y-X, Zhang D (2021) A new structure-preserving quaternion qr decomposition method for color image blind watermarking. Signal Process 185:108088
Wang X-Y, Shen X, Tian J-L, Niu P-P, Yang H-Y (2022) Statistical image watermark decoder using high-order difference coefficients and bounded generalized gaussian mixtures-based hmt. Signal Process 192:108371
Asikuzzaman M, Pickering MR (2018) An overview of digital video watermarking. IEEE Trans Circuits Syst Video Technol 28(9):2131–2153. https://doi.org/10.1109/TCSVT.2017.2712162
Asikuzzaman M, Mareen H, Moustafa N, Choo K-KR, Pickering MR (2022) Blind camcording-resistant video watermarking in the dtcwt and svd domain. IEEE Access 10:15681–15698. https://doi.org/10.1109/ACCESS.2022.3146723
Chen S, Malik A, Zhang X, Feng G, Wu H (2023) A fast method for robust video watermarking based on zernike moments. IEEE Trans Circ Syst Video Technol 1–1. https://doi.org/10.1109/TCSVT.2023.3281618
Malvar HS, Florêncio DA (2003) Improved spread spectrum: A new modulation technique for robust watermarking. IEEE Trans Signal Process 51(4):898–905
Valizadeh A, Wang ZJ (2010) Correlation-and-bit-aware spread spectrum embedding for data hiding. IEEE Trans Inf Forensics Secur 6(2):267–282
Zhang P, Xu S-Z, Yang H-Z (2012) Robust audio watermarking based on extended improved spread spectrum with perceptual masking. Int J Fuzzy Syst 14(2)
Zhang X, Wang ZJ (2013) Correlation-and-bit-aware multiplicative spread spectrum embedding for data hiding. In: 2013 IEEE International workshop on information forensics and security (WIFS), pp 186–190 . IEEE
Xiang Y, Natgunanathan I, Rong Y, Guo S (2015) Spread spectrum-based high embedding capacity watermarking method for audio signals. IEEE/ACM Trans Audio Speech Lang Process 23(12):2228–2237
Xiang Y, Natgunanathan I, Peng D, Hua G, Liu B (2017) Spread spectrum audio watermarking using multiple orthogonal pn sequences and variable embedding strengths and polarities. IEEE/ACM Trans Audio Speech Lang Process 26(3):529–539
Natgunanathan I, Xiang Y, Rong Y, Zhou W, Guo S (2012) Robust patchwork-based embedding and decoding scheme for digital audio watermarking. IEEE Trans Audio Speech Lang Process 20(8):2232–2239
Xiang Y, Natgunanathan I, Guo S, Zhou W, Nahavandi S (2014) Patchwork-based audio watermarking method robust to de-synchronization attacks. IEEE/ACM Trans Audio Speech Lang Process 22(9):1413–1423
Natgunanathan I, Xiang Y, Hua G, Beliakov G, Yearwood J (2017) Patchwork-based multilayer audio watermarking. IEEE/ACM Trans Audio Speech Lang Process 25(11):2176–2187
Liu Z, Huang Y, Huang J (2018) Patchwork-based audio watermarking robust against de-synchronization and recapturing attacks. IEEE Trans Inf Forensics Secur 14(5):1171–1180
Vivekananda BK, Sengupta I, Das A (2010) An adaptive audio watermarking based on the singular value decomposition in the wavelet domain - sciencedirect. Digital Signal Process 20(6):1547–1558
Lei B, Soon IY, Tan EL (2013) Robust svd-based audio watermarking scheme with differential evolution optimization. IEEE Trans Audio Speech Lang Process 21(11):2368–2378
Dhar PK, Shimamura T (2014) Blind svd-based audio watermarking using entropy and log-polar transformation. J Inform Sec Appl 20(C):74–83
Wu Q, Qu A, Huang D (2020) Robust and blind audio watermarking algorithm in dual domain for overcoming synchronization attacks. Math Probl Eng 2020:1–15
Zhao J, Zong T, Xiang Y, Gao L, Zhou W, Beliakov G (2021) Desynchronization attacks resilient watermarking method based on frequency singular value coefficient modification. IEEE/ACM Trans Audio Speech Lang Process 29:2282–2295. https://doi.org/10.1109/TASLP.2021.3092555
Jiang W, Huang X, Quan Y (2019) Audio watermarking algorithm against synchronization attacks using global characteristics and adaptive frame division. Signal Process 162
Benoraira A, Benmahammed K, Boucenna N (2015) Blind image watermarking technique based on differential embedding in dwt and dct domains. Eurasip J Adv Signal Process 2015(1):55
Saadi S, Merrad A, Benziane A (2019) Novel secured scheme for blind audio/speech norm-space watermarking by arnold algorithm. Signal Process 154(JAN):74–86
Bernardi G, Van Waterschoot T, Wouters J, Moonen M (2018) Subjective and objective sound-quality evaluation of adaptive feedback cancellation algorithms. IEEE/ACM Trans Audio Speech Lang Process 26(5):1–1
Torcoli M, Kastner T, Herre J (2021) Objective measures of perceptual audio quality reviewed: An evaluation of their application domain dependence. arXiv e-prints
Kabal P, et al (2002) An examination and interpretation of itu-r bs. 1387: Perceptual evaluation of audio quality. TSP Lab Technical Report, Dept. Electrical & Computer Engineering, McGill University, 1–89
Wang X, Wang P, Zhang P, Xu S, Yang H (2013) A norm-space, adaptive, and blind audio watermarking algorithm by discrete wavelet transform. Signal Processing
Li J-F, Wang H-X, Wu T, Sun X-M, Qian Q (2018) Norm ratio-based audio watermarking scheme in dwt domain. Multimed Tools Appl 77(12):14481–14497
Budiman G, Suksmono AB, Danudirdjo D (2020) Wavelet-based hybrid audio watermarking using statistical mean manipulation and spread spectrum. In: 2020 27th international conference on telecommunications (ICT), pp 1–5 . https://doi.org/10.1109/ICT49546.2020.9239581
Dhar PK (2015) A blind audio watermarking method based on lifting wavelet transform and qr decomposition. In: 2014 8th international conference on electrical and computer engineering (ICECE)
Acknowledgements
This study was supported by the Sichuan Science and Technology program (Grant nos.2023NSFSC0470, 2022YFG0152, 2021YFQ0053), and the National Natural Science Foundation of China (NSFC) program (No.62171387, No.62202390).
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Liu, X., Li, X., Shi, C. et al. A novel SVD-based adaptive robust audio watermarking algorithm. Multimed Tools Appl 83, 69443–69465 (2024). https://doi.org/10.1007/s11042-024-18340-7
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DOI: https://doi.org/10.1007/s11042-024-18340-7