Research Article
BibTex RIS Cite

Spread Embedding of Fragile Copyright Information to Protect Audio Signal

Year 2025, Volume: 9 Issue: 1, 125 - 134, 30.06.2025

Hüseyin Bilal Macit

https://doi.org/10.46460/ijiea.1645813

Abstract

Nowadays, millions of gigabytes of new data are generated every second and a large part of it is multimedia data. The security of this large amount of data is an important problem as well as its transmission and storage. Data without proven authenticity should not be distributed or used without permission. Audio data, unlike other types of multimedia, is quite weak in terms of copyright protection. Industrial practices generally prioritize the quality of audio data over the security of copyright data, contrary to academic recommendations. In this study, a spread hash-supported copyright embedding algorithm is proposed to ensure the copyright protection of audio data. The proposed algorithm is tested on a total of 92.017 seconds of dataset consisting of 516 music files and the results are presented. The algorithm successfully performs copyright verification of any 2-millisecond fragment of the audio in any clipping attack. Despite the changes made to the entire audio data, a 6% Bit Error Rate and 0.9999 Normalized Correlation values are obtained. According to international standards for perceptual evaluation of audio quality, a score of ~-1.7 is obtained in the objective evaluation. All performance evaluations are presented with tables and graphs, and comparisons are made with similar models in the literature. This study is one of the first to use a spread-hashing technique for audio copyright protection and has shown high performance, especially against clipping attacks.

Keywords

Copyright protection cyber security data security hash function

References

  • Duarte, F. (2024). Amount of data created Daily. Retrieved September 07, 2024 from https://explodingtopics.com/ blog/data-generated-per-day
  • Naqash, K. I., Malik, S. A., & Parah, S. A. (2024). Robust audio watermarking based on iterative filtering. Circuits Syst Signal Process, (43), 348–367.
  • Salah, E., Amine, K., Redouane, K., & Fares, K. (2021). A fourier transform based audio watermarking algorithm. Appl. Acoust, (172).
  • Kwon, O. J., Choi, S., & Lee, B. (2018). A watermark-based scheme for authenticating JPEG image integrity. IEEE Access, (6), 46194–46205.
  • Yalman, Y., & Ertürk, İ. (2009). Gerçek zamanlı video kayıtlarına veri gizleme uygulaması. XI. Akademik Bilişim Konferansı Bildirileri/Harran University, Şanlıurfa, (pp. 545-552).
  • Macit, H. B. (2019). Mobil cihaz görüntüleri için entropi tabanlı kırılgan damgalama metodu geliştirilmesi (Publication No. 566003) [Doctoral dissertation, Süleyman Demirel University, Isparta].
  • Arnold, M., Schmucker, M., & Wolthusen, S. D. (2003). Techniques and applications of digital watermarking and content protection. Artech House. London.
  • Arseven, M. (2019). Turkey provides access to copyright database. MA Gazette Edition, (78).
  • Al-Haj, A. (2014). An imperceptible and robust audio watermarking algorithm. J Audio Speech Music Proc., (37).
  • Wu, C. P., Su, P. C., & Kuo, C.-C. J. (2000). Robust and efficient digital audio watermarking using audio content analysis. Proceedings of SPIE 12th International Symposium Electronic Imaging, San Jose, CA, (pp. 382-392).
  • Tseng, H. W., & Leng, H. S. (2014). High-payload block-based data hiding scheme using hybrid edge detector with minimal distortion. EURASIP Journal on Audio, Speech, and Music Processing, (8)11, 647-654.
  • Bhattacharyya, S., Kundu, A., & Sanyal, G. (2011). A novel audio steganography technique by M16MA. International Journal of Computer Applications, (30)8, 26-34.
  • Acevedo, A. (2003). Digital watermarking for audio data in techniques and applications of digital watermarking and content protection. Artech House, USA. (75–114).
  • Rachid, R. S. (2014). Binary image watermarking on audio signal using wavelet transform (Publication No. 386090) [Master’s thesis, Çankaya University, Ankara]
  • Deshpande, D. (2021). Royalty-Free Audio Dataset. Retrieved September 02, 2024 from https://www.kaggle.com/datasets/darshan1504/royaltyfree-audio-dataset
  • Blau, Y., & Michaeli, T. (2019). Rethinking lossy compression: The rate-distortion-perception tradeoff. Proceedings of the International Conference on Machine Learning, (pp. 675–685).
  • Stankowski, J., Korzeniewski, C., Domański M., & Grajek, T. (2015). Rate-distortion optimized quantization in HEVC: Performance limitations. 2015 Picture Coding Symposium (PCS)/Cairns, QLD, Australia, (pp. 85-89).
  • Al-Darrat, K., & Abushaala, A. (2024). Copyright protection based on hybrid image watermark (DCT) with audio watermark (EMD). The International Journal of Engineering & Information Technology (IJEIT), 12(1), (pp. 84–89).
  • Aggarwal, K., & Verma, H. K. (2015). Hash_RC6 — Variable length Hash algorithm using RC6. Proceedings of 2015 International Conference on Advances in Computer Engineering and Applications, Ghaziabad, India, (pp. 450-456).
  • Pittalia, P. P. (2019). A comparative study of hash algorithms in cryptography. International Journal of Computer Science and Mobile Computing, (8)6, 147-152.
  • Barreto, P., & Rijmen, V. (2003). The Whirlpool hashing function, First open NESSIE Workshop, Leuven, Belgium, (pp. 13- 14).
  • Stallings, W. (2006). The Whirlpool secure hash function. Cryptologia, (30), (pp. 55–67).
  • Shannon, C. (1949). Communication theory of secrecy systems. Bell Systems Technical Journal, 28 (4), (pp. 656–715).
  • Kashifa, S., Tangeda, S., Sree, U. K., & Manikandan, V. M. (2023). Digital image watermarking and its applications: A detailed review. Proceedings of IEEE Int. Students’ Conf. Electr., Electron. Comput. Sci. (SCEECS), (pp. 1–7).
  • Ramyashree, Venugopala, P. S., Raghavendra, S., & Ashwini, B. (2024). CrypticCare: A strategic approach to telemedicine security using LSB and DCT steganography for enhancing the patient data protection. IEEE Access, (12), (pp. 101166 – 101183).
  • Chi, L., & Zhu, X. (2018). Hashing techniques: A survey and taxonomy. ACM Comput. Surveys, (50)1, (pp. 1–36).
  • Upadhyay, D., Gaikwad, N., Zaman, M., & Sampalli, S. (2022). Investigating the avalanche effect of various cryptographically secure hash functions and hash-based applications. IEEE Access, (10), (pp. 112472-112486).
  • Prodeus, A. (2015). Reducing sensitivity of segmental signal-to-noise ratio estimator to time-alignment error. International Journal of Electrical and Electronic Science, 2(2), (pp. 31-36).
  • Alsaad, S., & Hashim, E. (2013). A speech scrambler algorithm based on chaotic system. Al- Mustansiriyah J. Sci., (24), 357-372.
  • Salovarda, M., Bolkovac, I., & Domitrovic, H. (2005). Estimating perceptual audio system quality using PEAQ algorithm, 18th International Conference on Applied Electromagnetics and Communications, Dubrovnik, Croatia, 1-4
  • Thiede, T., Treurniet, W. C., Bitto, R., Schmidmer, C., Sporer, T., Beerends, J. G., Colomes, C., Keyhl, M., Stoll, G., Brandenburg, K., & Feiten, B. (2000). PEAQ the ITU standard for objective measurement of perceived audio quality. J.Audio Eng.Soc., (48)1/2, 3-29.
  • Zeng, Y., Mao, H., & Peng, D. (2019). Spectrogram based multi-task audio classification. Multimed Tools Appl, (78), 3705–3722
  • Kalantarian, H., Alshurafa, N., Pourhomayoun, M., Sarin, S., Le, T., & Sarrafzadeh, M. (2014). Spectrogram-based audio classification of nutrition intake, 2014 Health Innovations and Point-of-Care Technologies Conference, Seattle, Washington USA, 161-164.
  • Zhang, G., Zheng, L. Su, Z., Zeng Y., & Wang, G. (2023). M-Sequences and sliding window-based audio watermarking robust against large-scale cropping attacks. IEEE Transactions on Information Forensics and Security, (18), 1182-1195.
  • Korany, N. O., Elboghdadly, N. M. & Elabdein, M. Z. (2024). High capacity, secure audio watermarking technique integrating spread spectrum and linear predictive coding. Multimed Tools Appl, (83), 50645–50668.
  • Hua, G. Huang, J. Shi, Y.Q., Goh, J., Thing, V.L.L. (2016). Twenty years of digital audio watermarking-a comprehensive review, Signal Processing, (128), 222-242.
  • Cox, I.J., Kilian, J., Leighton, F.T., Shamoon, T. (1997). Secure spread spectrum watermarking for multimedia, IEEE Trans. Image Process., 6(12), 1673-1687.
  • Yeo, I.K., Kim, H.J. (2003). Modified patchwork algorithm: a novel audio watermarking scheme, IEEE Speech Audio Process., 11(4), 381–386.

Ses Sinyalini Korumak İçin Kırılgan Telif Hakkı Bilgilerinin Yaygın Gömülmesi

Year 2025, Volume: 9 Issue: 1, 125 - 134, 30.06.2025

Hüseyin Bilal Macit

https://doi.org/10.46460/ijiea.1645813

Abstract

Günümüzde her saniye milyonlarca gigabayt yeni veri üretilmektedir ve bunun büyük bir kısmı multimedya verisidir. Bu büyüklükte verinin iletilmesi ve depolanması kadar güvenliği de önemli bir problemdir. Aidiyeti kanıtlanmamış veri izinsiz dağıtılmamalı ve kullanılmamalıdır. Ses verisi, diğer multimedya türlerinin aksine telif hakkı korunması konusunda oldukça güçsüzdür. Endüstriyel uygulamalar genellikle akademik önerilerin aksine telif hakkı verisinin güvenliğinden ziyade ses verisinin kalitesine önem verir. Bu çalışmada, ses verilerinin telif hakkı güvenliğini sağlamak için hash destekli yaygın bir telif hakkı gömme algoritması önerilmiştir. Önerilen algoritma 516 müzik dosyasından oluşan toplam 92,017 saniyelik bir veri seti üzerinde test edilmiş ve sonuçları sunulmuştur. Algoritma herhangi bir kırpma saldırısında sesin herhangi 2 milisaniyelik parçasından bile telif doğrulamasını başarıyla gerçekleştirmiştir. Tüm ses verisinde yapılan değişikliğe rağmen %6 Bit Hata Oranı ve 0,9999 Normalize Korelasyon değerleri elde edilmiştir. Uluslararası ses kalitesinin algısal değerlendirmesi standartlarına göre nesnel değerlendirmede ~-1,7 skor elde edilmiştir. Tüm performans değerlendirmeleri tablolar ve grafikler ile sunulmuş, literatürdeki benzer modeller ile karşılaştırma yapılmıştır. Bu çalışma, ses sinyalinin telif hakkını korumak için bir yaygın-çırpı tekniği kullanan ilk çalışmalardandır ve özellikle kırpma saldırılarına karşı yüksek performans göstermiştir.

Keywords

çırpı fonksiyonu telif hakkı koruması siber güvenlik veri güvenliği

References

  • Duarte, F. (2024). Amount of data created Daily. Retrieved September 07, 2024 from https://explodingtopics.com/ blog/data-generated-per-day
  • Naqash, K. I., Malik, S. A., & Parah, S. A. (2024). Robust audio watermarking based on iterative filtering. Circuits Syst Signal Process, (43), 348–367.
  • Salah, E., Amine, K., Redouane, K., & Fares, K. (2021). A fourier transform based audio watermarking algorithm. Appl. Acoust, (172).
  • Kwon, O. J., Choi, S., & Lee, B. (2018). A watermark-based scheme for authenticating JPEG image integrity. IEEE Access, (6), 46194–46205.
  • Yalman, Y., & Ertürk, İ. (2009). Gerçek zamanlı video kayıtlarına veri gizleme uygulaması. XI. Akademik Bilişim Konferansı Bildirileri/Harran University, Şanlıurfa, (pp. 545-552).
  • Macit, H. B. (2019). Mobil cihaz görüntüleri için entropi tabanlı kırılgan damgalama metodu geliştirilmesi (Publication No. 566003) [Doctoral dissertation, Süleyman Demirel University, Isparta].
  • Arnold, M., Schmucker, M., & Wolthusen, S. D. (2003). Techniques and applications of digital watermarking and content protection. Artech House. London.
  • Arseven, M. (2019). Turkey provides access to copyright database. MA Gazette Edition, (78).
  • Al-Haj, A. (2014). An imperceptible and robust audio watermarking algorithm. J Audio Speech Music Proc., (37).
  • Wu, C. P., Su, P. C., & Kuo, C.-C. J. (2000). Robust and efficient digital audio watermarking using audio content analysis. Proceedings of SPIE 12th International Symposium Electronic Imaging, San Jose, CA, (pp. 382-392).
  • Tseng, H. W., & Leng, H. S. (2014). High-payload block-based data hiding scheme using hybrid edge detector with minimal distortion. EURASIP Journal on Audio, Speech, and Music Processing, (8)11, 647-654.
  • Bhattacharyya, S., Kundu, A., & Sanyal, G. (2011). A novel audio steganography technique by M16MA. International Journal of Computer Applications, (30)8, 26-34.
  • Acevedo, A. (2003). Digital watermarking for audio data in techniques and applications of digital watermarking and content protection. Artech House, USA. (75–114).
  • Rachid, R. S. (2014). Binary image watermarking on audio signal using wavelet transform (Publication No. 386090) [Master’s thesis, Çankaya University, Ankara]
  • Deshpande, D. (2021). Royalty-Free Audio Dataset. Retrieved September 02, 2024 from https://www.kaggle.com/datasets/darshan1504/royaltyfree-audio-dataset
  • Blau, Y., & Michaeli, T. (2019). Rethinking lossy compression: The rate-distortion-perception tradeoff. Proceedings of the International Conference on Machine Learning, (pp. 675–685).
  • Stankowski, J., Korzeniewski, C., Domański M., & Grajek, T. (2015). Rate-distortion optimized quantization in HEVC: Performance limitations. 2015 Picture Coding Symposium (PCS)/Cairns, QLD, Australia, (pp. 85-89).
  • Al-Darrat, K., & Abushaala, A. (2024). Copyright protection based on hybrid image watermark (DCT) with audio watermark (EMD). The International Journal of Engineering & Information Technology (IJEIT), 12(1), (pp. 84–89).
  • Aggarwal, K., & Verma, H. K. (2015). Hash_RC6 — Variable length Hash algorithm using RC6. Proceedings of 2015 International Conference on Advances in Computer Engineering and Applications, Ghaziabad, India, (pp. 450-456).
  • Pittalia, P. P. (2019). A comparative study of hash algorithms in cryptography. International Journal of Computer Science and Mobile Computing, (8)6, 147-152.
  • Barreto, P., & Rijmen, V. (2003). The Whirlpool hashing function, First open NESSIE Workshop, Leuven, Belgium, (pp. 13- 14).
  • Stallings, W. (2006). The Whirlpool secure hash function. Cryptologia, (30), (pp. 55–67).
  • Shannon, C. (1949). Communication theory of secrecy systems. Bell Systems Technical Journal, 28 (4), (pp. 656–715).
  • Kashifa, S., Tangeda, S., Sree, U. K., & Manikandan, V. M. (2023). Digital image watermarking and its applications: A detailed review. Proceedings of IEEE Int. Students’ Conf. Electr., Electron. Comput. Sci. (SCEECS), (pp. 1–7).
  • Ramyashree, Venugopala, P. S., Raghavendra, S., & Ashwini, B. (2024). CrypticCare: A strategic approach to telemedicine security using LSB and DCT steganography for enhancing the patient data protection. IEEE Access, (12), (pp. 101166 – 101183).
  • Chi, L., & Zhu, X. (2018). Hashing techniques: A survey and taxonomy. ACM Comput. Surveys, (50)1, (pp. 1–36).
  • Upadhyay, D., Gaikwad, N., Zaman, M., & Sampalli, S. (2022). Investigating the avalanche effect of various cryptographically secure hash functions and hash-based applications. IEEE Access, (10), (pp. 112472-112486).
  • Prodeus, A. (2015). Reducing sensitivity of segmental signal-to-noise ratio estimator to time-alignment error. International Journal of Electrical and Electronic Science, 2(2), (pp. 31-36).
  • Alsaad, S., & Hashim, E. (2013). A speech scrambler algorithm based on chaotic system. Al- Mustansiriyah J. Sci., (24), 357-372.
  • Salovarda, M., Bolkovac, I., & Domitrovic, H. (2005). Estimating perceptual audio system quality using PEAQ algorithm, 18th International Conference on Applied Electromagnetics and Communications, Dubrovnik, Croatia, 1-4
  • Thiede, T., Treurniet, W. C., Bitto, R., Schmidmer, C., Sporer, T., Beerends, J. G., Colomes, C., Keyhl, M., Stoll, G., Brandenburg, K., & Feiten, B. (2000). PEAQ the ITU standard for objective measurement of perceived audio quality. J.Audio Eng.Soc., (48)1/2, 3-29.
  • Zeng, Y., Mao, H., & Peng, D. (2019). Spectrogram based multi-task audio classification. Multimed Tools Appl, (78), 3705–3722
  • Kalantarian, H., Alshurafa, N., Pourhomayoun, M., Sarin, S., Le, T., & Sarrafzadeh, M. (2014). Spectrogram-based audio classification of nutrition intake, 2014 Health Innovations and Point-of-Care Technologies Conference, Seattle, Washington USA, 161-164.
  • Zhang, G., Zheng, L. Su, Z., Zeng Y., & Wang, G. (2023). M-Sequences and sliding window-based audio watermarking robust against large-scale cropping attacks. IEEE Transactions on Information Forensics and Security, (18), 1182-1195.
  • Korany, N. O., Elboghdadly, N. M. & Elabdein, M. Z. (2024). High capacity, secure audio watermarking technique integrating spread spectrum and linear predictive coding. Multimed Tools Appl, (83), 50645–50668.
  • Hua, G. Huang, J. Shi, Y.Q., Goh, J., Thing, V.L.L. (2016). Twenty years of digital audio watermarking-a comprehensive review, Signal Processing, (128), 222-242.
  • Cox, I.J., Kilian, J., Leighton, F.T., Shamoon, T. (1997). Secure spread spectrum watermarking for multimedia, IEEE Trans. Image Process., 6(12), 1673-1687.
  • Yeo, I.K., Kim, H.J. (2003). Modified patchwork algorithm: a novel audio watermarking scheme, IEEE Speech Audio Process., 11(4), 381–386.
There are 38 citations in total.

Details

Primary Language English
Subjects Computer Software, Software Engineering (Other)
Journal Section Articles
Authors

Hüseyin Bilal Macit 0000-0002-5325-5416

Early Pub Date June 30, 2025
Publication Date June 30, 2025
Submission Date February 24, 2025
Acceptance Date June 16, 2025
Published in Issue Year 2025 Volume: 9 Issue: 1

Cite

APA Macit, H. B. (2025). Spread Embedding of Fragile Copyright Information to Protect Audio Signal. International Journal of Innovative Engineering Applications, 9(1), 125-134. https://doi.org/10.46460/ijiea.1645813
AMA Macit HB. Spread Embedding of Fragile Copyright Information to Protect Audio Signal. IJIEA. June 2025;9(1):125-134. doi:10.46460/ijiea.1645813
Chicago Macit, Hüseyin Bilal. “Spread Embedding of Fragile Copyright Information to Protect Audio Signal”. International Journal of Innovative Engineering Applications 9, no. 1 (June 2025): 125-34. https://doi.org/10.46460/ijiea.1645813.
EndNote Macit HB (June 1, 2025) Spread Embedding of Fragile Copyright Information to Protect Audio Signal. International Journal of Innovative Engineering Applications 9 1 125–134.
IEEE H. B. Macit, “Spread Embedding of Fragile Copyright Information to Protect Audio Signal”, IJIEA, vol. 9, no. 1, pp. 125–134, 2025, doi: 10.46460/ijiea.1645813.
ISNAD Macit, Hüseyin Bilal. “Spread Embedding of Fragile Copyright Information to Protect Audio Signal”. International Journal of Innovative Engineering Applications 9/1 (June 2025), 125-134. https://doi.org/10.46460/ijiea.1645813.
JAMA Macit HB. Spread Embedding of Fragile Copyright Information to Protect Audio Signal. IJIEA. 2025;9:125–134.
MLA Macit, Hüseyin Bilal. “Spread Embedding of Fragile Copyright Information to Protect Audio Signal”. International Journal of Innovative Engineering Applications, vol. 9, no. 1, 2025, pp. 125-34, doi:10.46460/ijiea.1645813.
Vancouver Macit HB. Spread Embedding of Fragile Copyright Information to Protect Audio Signal. IJIEA. 2025;9(1):125-34.
 Download Cover Image

This work is licensed under CC BY-NC 4.0