Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

Design of Audio Digital Watermarking System Resistant to Removal Attack

, ,

DOI: http://dx.doi.org/10.15439/2017F99

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 647652 ()

Full text

Abstract. We consider a digital watermarking system intended for an embedding of additional information into audio (typically musical) files that should be resistant against a removal attack. The proposed embedding procedure is based on a reverberation and extraction procedure executing a cepstral transform. A removal attack based on blind dereverberation is investigated both theoretically and experimentally. In order to prevent such an attack, a slight modification of the embedding procedure is also proposed. Further experiments show that the proposed watermarking system provides both a good quality of the cover audio-signal and a sufficiently large embedding rate.


  1. M. Arnold, P. G. Baum, and W. Voeßing, “Information hiding,” S. Katzenbeisser and A.-R. Sadeghi, Eds. Berlin, Heidelberg: Springer-Verlag, 2009, ch. A Phase Modulation Audio Watermarking Technique, pp. 102–116, http://dx.doi.org/10.1007/978-3-642-04431-1_8. [Online]. Available: http://dx.doi.org/10.1007/978-3-642-04431-1_8
  2. V. I. Korzhik, G. Morales-Luna, and I. Fedyanin, “Audio watermarking based on echo hiding with zero error probability.” International Journal of Computer Science and Applications, vol. 10, no. 1, pp. 1–10, 2013.
  3. V. Alekseyev, A. Grudinin, and V. Korzhik, “Design of robust audio watermark system,” in Proceedings of the XI International Symposium on Problems of Redundancy in Information and Control Systems, Aug 2007, pp. 163–165.
  4. H. Liu and W. Zhang, “Overview of audio watermarking algorithm against synchronization attacks,” in Advances in Intelligent Systems Research: ICAITA-16, Aug 2016, http://dx.doi.org/10.2991/icaita-16.2016.52.
  5. J. M. Arend and C. Pörschmann, “Audio watermarking of binaural room impulse responses,” in Audio Engineering Society Conference: 2016 AES International Conference on Headphone Technology, Aug 2016, http://dx.doi.org/10.17743/aesconf.2016.978-1-942220-09-1. [Online]. Available: http://www.aes.org/e-lib/browse.cfm?elib=18346
  6. J. Proakis, Digital Communications, Fourth Edition. Mc Graw Hill, 2001.
  7. D. G. Childers, D. P. Skinner, and R. C. Kemerait, “The cepstrum: A guide to processing,” Proceedings of the IEEE, vol. 65, pp. 1428–1443, 1977, http://dx.doi.org/10.1109/PROC.1977.10747.
  8. T. Nakatani, M. Miyoshi, and K. Kinoshita, “One microphone blind dereverberation based on quasi-periodicity of speech signals,” in Advances in Neural Information Processing Systems 16, S. Thrun, L. Saul, and B. Schölkopf, Eds. Cambridge, MA: MIT Press, 2003, p. None. [Online]. Available: http://books.nips.cc/papers/files/nips16/NIPS2003_SP06.pdf
  9. C. Evers, “Blind dereverberation of speech from moving and stationary speakers using sequential Monte Carlo methods,” Ph.D. dissertation, The University of Edinburgh (United Kingdom, 2010.
  10. H. Attias, J. Platt, A. Acero, and L. Deng, “Speech denoising and dereverberation using probabilistic models,” November 2000. [Online]. Available: https://www.microsoft.com/en-us/research/publication/speech-denoising-and-dereverberation-using-probabilistic-models/
  11. N. Cvejic and T. Seppanen, Digital Audio Watermarking Techniques and Technologies: Applications and Benchmarks. Hershey, PA, USA: IGI Global, 2007, http://dx.doi.org/10.4018/978-1-59904-513-9.
  12. G. Chardon, T. Nowakowski, J. de Rosny, and L. Daudet, “A blind dereverberation method for narrowband source localization,” IEEE Journal of Selected Topics in Signal Processing, vol. 9, no. 5, pp. 815–824, Aug 2015, http://dx.doi.org/10.1109/JSTSP.2015.2422673.
  13. K. Imoto and N. Ono, “Spatial cepstrum as a spatial feature using a distributed microphone array for acoustic scene analysis,” IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 25, no. 6, pp. 1335–1343, 2017, http://dx.doi.org/10.1109/TASLP.2017.269059.