An effective digital audio watermarking using a deep convolutional neural network with a search location optimization algorithm for improvement in Robustness and Imperceptibility
Watermarking is the advanced technology utilized to secure digital data by integrating ownership or copyright protection. Most of the traditional extracting processes in audio watermarking have some restrictions due to low reliability to various attacks. Hence, a deep learning-based audio watermarki...
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| Vydáno v: | High-Confidence Computing Ročník 3; číslo 4; s. 100153 |
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| Jazyk: | angličtina |
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Elsevier B.V
01.12.2023
Elsevier |
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| ISSN: | 2667-2952, 2667-2952 |
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| Abstract | Watermarking is the advanced technology utilized to secure digital data by integrating ownership or copyright protection. Most of the traditional extracting processes in audio watermarking have some restrictions due to low reliability to various attacks. Hence, a deep learning-based audio watermarking system is proposed in this research to overcome the restriction in the traditional methods. The implication of the research relies on enhancing the performance of the watermarking system using the Discrete Wavelet Transform (DWT) and the optimized deep learning technique. The selection of optimal embedding location is the research contribution that is carried out by the deep convolutional neural network (DCNN). The hyperparameter tuning is performed by the so-called search location optimization, which minimizes the errors in the classifier. The experimental result reveals that the proposed digital audio watermarking system provides better robustness and performance in terms of Bit Error Rate (BER), Mean Square Error (MSE), and Signal-to-noise ratio. The BER, MSE, and SNR of the proposed audio watermarking model without the noise are 0.082, 0.099, and 45.363 respectively, which is found to be better performance than the existing watermarking models. |
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| AbstractList | Watermarking is the advanced technology utilized to secure digital data by integrating ownership or copyright protection. Most of the traditional extracting processes in audio watermarking have some restrictions due to low reliability to various attacks. Hence, a deep learning-based audio watermarking system is proposed in this research to overcome the restriction in the traditional methods. The implication of the research relies on enhancing the performance of the watermarking system using the Discrete Wavelet Transform (DWT) and the optimized deep learning technique. The selection of optimal embedding location is the research contribution that is carried out by the deep convolutional neural network (DCNN). The hyperparameter tuning is performed by the so-called search location optimization, which minimizes the errors in the classifier. The experimental result reveals that the proposed digital audio watermarking system provides better robustness and performance in terms of Bit Error Rate (BER), Mean Square Error (MSE), and Signal-to-noise ratio. The BER, MSE, and SNR of the proposed audio watermarking model without the noise are 0.082, 0.099, and 45.363 respectively, which is found to be better performance than the existing watermarking models. |
| ArticleNumber | 100153 |
| Author | Patil, Abhijit J. Shelke, Ramesh |
| Author_xml | – sequence: 1 givenname: Abhijit J. surname: Patil fullname: Patil, Abhijit J. email: abhijitjp774@gmail.com organization: Computer Engineering, Pacific Academy of Higher Education and Research University, Udaipur 313003, India – sequence: 2 givenname: Ramesh surname: Shelke fullname: Shelke, Ramesh organization: Electronics and Telecommunications, Pacific Academy of Higher Education and Research University, Udaipur 313003, India |
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| Cites_doi | 10.1007/s10489-017-0903-6 10.1007/978-3-030-03748-2_8 10.1007/978-3-642-17499-5_6 10.1007/s00521-019-04434-z 10.1007/s00500-017-2489-7 10.1049/iet-spr.2014.0388 10.1007/s00521-016-2788-4 10.1109/TSP.2018.8441174 10.1007/s11042-019-7214-3 10.1007/s00521-020-05389-2 10.1109/79.939835 10.18178/ijmlc.2020.10.2.932 10.1109/TEVC.2009.2011992 10.1007/s10772-015-9318-0 10.1109/TKDE.2018.2851517 |
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| Keywords | Search location optimization algorithm DWT Imperceptibility Robustness Deep convolutional neural network |
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| References | Hu, Zhao, Zheng (b5) 2018; 31 Pourhashemi, Mosleh, Erfani (b9) 2021; 33 M.K. Dutta, V.K. Pathak, P. Gupta, An adaptive robust watermarking algorithm for audio signals using SVD, in: Proceedings of Transactions on Computational Science Vol. X, 2010, pp. 131–153. Merrer, Perez, Trédan (b18) 2020; 32 Deeba, Kun, Dharejo, Langah, Memon (b6) 2020; 10 Galajit, Karnjana, Unoki, Aimmanee (b1) 2019 Garg, Kishore (b2) 2021 Latifpour, Mosleh, Kheyrandish (b13) 2015; 18 Karajeh, Khatib, Rajab, Maqableh (b3) 2019; 78 Sun, Xu, Liu, Zhang, Li, Shen (b8) 2018; 30 Ferdowsi, Saad (b19) 2018 . Podilchuk, Delp (b11) 2001; 18 Li, Xu, Yang (b12) 2016; 10 BraTS dataset K. Galajit, J. Karnjana, P. Aimmanee, M. Unoki, Digital audio watermarking method based on singular spectrum analysis with automatic parameter estimation using a convolutional neural network, in: Proceedings of International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2018, pp. 63–73. Mousavirad, Ebrahimpour-Komleh (b15) 2017; 47 A. Kaur, M.K. Dutta, J. Prinosil, General regression neural network based audio watermarking algorithm using torus automorphism, in: Proceedings of 41st International Conference on Telecommunications and Signal Processing (TSP), 2018, pp. 1–4. Ingaleshwar, Dharwadkar (b20) 2021 Su, Chen (b10) 2018; 22 He, Wu, Saunders (b16) 2009; 13 Podilchuk (10.1016/j.hcc.2023.100153_b11) 2001; 18 Garg (10.1016/j.hcc.2023.100153_b2) 2021 10.1016/j.hcc.2023.100153_b17 Su (10.1016/j.hcc.2023.100153_b10) 2018; 22 Merrer (10.1016/j.hcc.2023.100153_b18) 2020; 32 Deeba (10.1016/j.hcc.2023.100153_b6) 2020; 10 Li (10.1016/j.hcc.2023.100153_b12) 2016; 10 Hu (10.1016/j.hcc.2023.100153_b5) 2018; 31 Ferdowsi (10.1016/j.hcc.2023.100153_b19) 2018 He (10.1016/j.hcc.2023.100153_b16) 2009; 13 10.1016/j.hcc.2023.100153_b7 10.1016/j.hcc.2023.100153_b14 Karajeh (10.1016/j.hcc.2023.100153_b3) 2019; 78 Sun (10.1016/j.hcc.2023.100153_b8) 2018; 30 Mousavirad (10.1016/j.hcc.2023.100153_b15) 2017; 47 Galajit (10.1016/j.hcc.2023.100153_b1) 2019 10.1016/j.hcc.2023.100153_b4 Pourhashemi (10.1016/j.hcc.2023.100153_b9) 2021; 33 Latifpour (10.1016/j.hcc.2023.100153_b13) 2015; 18 Ingaleshwar (10.1016/j.hcc.2023.100153_b20) 2021 |
| References_xml | – volume: 30 start-page: 2425 year: 2018 end-page: 2440 ident: b8 article-title: A robust image watermarking scheme using Arnold transform and BP neural network publication-title: Neural Comput. Appl. – volume: 18 start-page: 33 year: 2001 end-page: 46 ident: b11 article-title: Digital watermarking: algorithms and applications publication-title: IEEE Signal Process. Mag. – volume: 33 start-page: 6161 year: 2021 end-page: 6181 ident: b9 article-title: A novel audio watermarking scheme using ensemble-based watermark detector and DWT publication-title: Neural Comput. Appl. – reference: M.K. Dutta, V.K. Pathak, P. Gupta, An adaptive robust watermarking algorithm for audio signals using SVD, in: Proceedings of Transactions on Computational Science Vol. X, 2010, pp. 131–153. – volume: 13 start-page: 973 year: 2009 end-page: 990 ident: b16 article-title: Group search optimizer: an optimization algorithm inspired by animal searching behavior publication-title: IEEE Trans. Evol. Comput. – start-page: 1 year: 2018 end-page: 6 ident: b19 article-title: Deep learning-based dynamic watermarking for secure signal authentication in the Internet of Things publication-title: 2018 IEEE International Conference on Communications (ICC) – start-page: 1 year: 2021 end-page: 25 ident: b20 article-title: Water chaotic fruit fly optimization-based deep convolutional neural network for image watermarking using wavelet transform publication-title: Multimedia Tools Appl. – volume: 10 start-page: 266 year: 2016 end-page: 273 ident: b12 article-title: Spread spectrum audio watermarking based on perceptual characteristic aware extraction publication-title: IET Signal Process. – volume: 10 start-page: 277 year: 2020 end-page: 282 ident: b6 article-title: Digital watermarking using deep neural network publication-title: Int. J. Mach. Learn. Comput. – reference: K. Galajit, J. Karnjana, P. Aimmanee, M. Unoki, Digital audio watermarking method based on singular spectrum analysis with automatic parameter estimation using a convolutional neural network, in: Proceedings of International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2018, pp. 63–73. – reference: . – reference: A. Kaur, M.K. Dutta, J. Prinosil, General regression neural network based audio watermarking algorithm using torus automorphism, in: Proceedings of 41st International Conference on Telecommunications and Signal Processing (TSP), 2018, pp. 1–4. – start-page: 1 year: 2021 end-page: 18 ident: b2 article-title: An efficient and secured blind image watermarking using ABC optimization in DWT and DCT domain publication-title: Multimedia Tools Appl. – volume: 78 start-page: 18395 year: 2019 end-page: 18418 ident: b3 article-title: A robust digital audio watermarking scheme based on DWT and Schur decomposition publication-title: Multimedia Tools Appl. – volume: 47 start-page: 850 year: 2017 end-page: 887 ident: b15 article-title: Human mental search: a new population-based metaheuristic optimization algorithm publication-title: Appl. Intell. – volume: 31 start-page: 1024 year: 2018 end-page: 1037 ident: b5 article-title: A new robust approach for reversible database watermarking with distortion control publication-title: IEEE Trans. Knowl. Data Eng. – volume: 22 start-page: 91 year: 2018 end-page: 106 ident: b10 article-title: Robust color image watermarking technique in the spatial domain publication-title: Soft Comput. – reference: BraTS dataset, – year: 2019 ident: b1 article-title: Semi-fragile speech watermarking based on singular-spectrum analysis with CNN-based parameter estimation for tampering detection publication-title: APSIPA Trans. Signal Inf. Process. – volume: 18 start-page: 697 year: 2015 end-page: 706 ident: b13 article-title: An intelligent audio watermarking based on KNN learning algorithm publication-title: Int. J. Speech Technol. – volume: 32 start-page: 9233 year: 2020 end-page: 9244 ident: b18 article-title: Adversarial frontier stitching for remote neural network watermarking publication-title: Neural Comput. Appl. – volume: 47 start-page: 850 issue: 3 year: 2017 ident: 10.1016/j.hcc.2023.100153_b15 article-title: Human mental search: a new population-based metaheuristic optimization algorithm publication-title: Appl. Intell. doi: 10.1007/s10489-017-0903-6 – ident: 10.1016/j.hcc.2023.100153_b4 doi: 10.1007/978-3-030-03748-2_8 – issue: 8 year: 2019 ident: 10.1016/j.hcc.2023.100153_b1 article-title: Semi-fragile speech watermarking based on singular-spectrum analysis with CNN-based parameter estimation for tampering detection publication-title: APSIPA Trans. Signal Inf. Process. – ident: 10.1016/j.hcc.2023.100153_b14 doi: 10.1007/978-3-642-17499-5_6 – start-page: 1 year: 2021 ident: 10.1016/j.hcc.2023.100153_b20 article-title: Water chaotic fruit fly optimization-based deep convolutional neural network for image watermarking using wavelet transform publication-title: Multimedia Tools Appl. – volume: 32 start-page: 9233 issue: 13 year: 2020 ident: 10.1016/j.hcc.2023.100153_b18 article-title: Adversarial frontier stitching for remote neural network watermarking publication-title: Neural Comput. Appl. doi: 10.1007/s00521-019-04434-z – volume: 22 start-page: 91 year: 2018 ident: 10.1016/j.hcc.2023.100153_b10 article-title: Robust color image watermarking technique in the spatial domain publication-title: Soft Comput. doi: 10.1007/s00500-017-2489-7 – volume: 10 start-page: 266 issue: 3 year: 2016 ident: 10.1016/j.hcc.2023.100153_b12 article-title: Spread spectrum audio watermarking based on perceptual characteristic aware extraction publication-title: IET Signal Process. doi: 10.1049/iet-spr.2014.0388 – volume: 30 start-page: 2425 issue: 8 year: 2018 ident: 10.1016/j.hcc.2023.100153_b8 article-title: A robust image watermarking scheme using Arnold transform and BP neural network publication-title: Neural Comput. Appl. doi: 10.1007/s00521-016-2788-4 – ident: 10.1016/j.hcc.2023.100153_b7 doi: 10.1109/TSP.2018.8441174 – ident: 10.1016/j.hcc.2023.100153_b17 – volume: 78 start-page: 18395 issue: 13 year: 2019 ident: 10.1016/j.hcc.2023.100153_b3 article-title: A robust digital audio watermarking scheme based on DWT and Schur decomposition publication-title: Multimedia Tools Appl. doi: 10.1007/s11042-019-7214-3 – start-page: 1 year: 2021 ident: 10.1016/j.hcc.2023.100153_b2 article-title: An efficient and secured blind image watermarking using ABC optimization in DWT and DCT domain publication-title: Multimedia Tools Appl. – start-page: 1 year: 2018 ident: 10.1016/j.hcc.2023.100153_b19 article-title: Deep learning-based dynamic watermarking for secure signal authentication in the Internet of Things – volume: 33 start-page: 6161 issue: 11 year: 2021 ident: 10.1016/j.hcc.2023.100153_b9 article-title: A novel audio watermarking scheme using ensemble-based watermark detector and DWT publication-title: Neural Comput. Appl. doi: 10.1007/s00521-020-05389-2 – volume: 18 start-page: 33 issue: 4 year: 2001 ident: 10.1016/j.hcc.2023.100153_b11 article-title: Digital watermarking: algorithms and applications publication-title: IEEE Signal Process. Mag. doi: 10.1109/79.939835 – volume: 10 start-page: 277 issue: 2 year: 2020 ident: 10.1016/j.hcc.2023.100153_b6 article-title: Digital watermarking using deep neural network publication-title: Int. J. Mach. Learn. Comput. doi: 10.18178/ijmlc.2020.10.2.932 – volume: 13 start-page: 973 issue: 5 year: 2009 ident: 10.1016/j.hcc.2023.100153_b16 article-title: Group search optimizer: an optimization algorithm inspired by animal searching behavior publication-title: IEEE Trans. Evol. Comput. doi: 10.1109/TEVC.2009.2011992 – volume: 18 start-page: 697 issue: 4 year: 2015 ident: 10.1016/j.hcc.2023.100153_b13 article-title: An intelligent audio watermarking based on KNN learning algorithm publication-title: Int. J. Speech Technol. doi: 10.1007/s10772-015-9318-0 – volume: 31 start-page: 1024 issue: 6 year: 2018 ident: 10.1016/j.hcc.2023.100153_b5 article-title: A new robust approach for reversible database watermarking with distortion control publication-title: IEEE Trans. Knowl. Data Eng. doi: 10.1109/TKDE.2018.2851517 |
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