Advertisement

Co-utility pp 87-116 | Cite as

Co-utile Privacy-Aware P2P Content Distribution

  • David MegíasEmail author
  • Josep Domingo-Ferrer
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 110)

Abstract

Multicast distribution of content is not suited to content-based electronic commerce because all buyers obtain exactly the same copy of the content, in such a way that unlawful redistributors cannot be traced. Unicast distribution has the shortcoming of requiring one connection with each buyer, but it allows the merchant to embed a different serial number in the copy obtained by each buyer, which enables redistributor tracing. Peer-to-peer (P2P) distribution is a third option which may combine some of the advantages of multicast and unicast: on the one hand, the merchant only needs unicast connections with a few seed buyers, who take over the task of further spreading the content; on the other hand, if a proper fingerprinting mechanism is used, unlawful redistributors of the P2P distributed content can still be traced. In this chapter, we describe a co-utile fingerprinting mechanism for P2P content distribution which allows redistributor tracing, while preserving the privacy of most honest buyers and offering collusion resistance and buyer frameproofness.

Notes

Acknowledgements

Funding by the Templeton World Charity Foundation (grant TWCF0095/AB60 “CO-UTILITY”) is gratefully acknowledged. Also, partial support to this work has been received from the Government of Catalonia (ICREA Acadèmia Prize to J. Domingo-Ferrer and grant 2014 SGR 537), the Spanish Government (projects TIN2014-57364-C2-1-R “SmartGlacis”, TIN2015-70054-REDC and TIN2016-80250-R “Sec-MCloud”) and the European Commission (projects H2020-644024 “CLARUS” and H2020-700540 “CANVAS”). The authors are with the UNESCO Chair in Data Privacy, but the views in this work are the authors’ own and are not necessarily shared by UNESCO or any of the funding bodies.

References

  1. 1.
    Bo, Y., Piyuan, L., Wenzheng, Z.: An efficient anonymous fingerprinting protocol. In: Computational Intelligence and Security, LNCS, vol. 4456, pp. 824–832. Springer, Berlin (2007)Google Scholar
  2. 2.
    Boneh, D., Shaw, J.: Collusion-secure fingerprinting for digital data. In: Advances in Cryptology, LNCS, vol. 963, pp. 452–465. Springer, Berlin (1995)Google Scholar
  3. 3.
    Camenisch, J.: Efficient anonymous fingerprinting with group signatures. In: Asiacrypt, LNCS, vol. 1976, pp. 415–428. Springer, Berlin (2000)Google Scholar
  4. 4.
    Chang, C.-C., Tsai, H.-C., Hsieh, Y.-P.: An efficient and fair buyer-seller fingerprinting scheme for large scale networks. Comput. Secur. 29(2), 269–277 (2010)CrossRefGoogle Scholar
  5. 5.
    Chaum, D.L.: Untraceable electronic mail, return addresses, and digital pseudonyms. Commun. ACM 24(2), 84–90 (1981)CrossRefGoogle Scholar
  6. 6.
    Cox, I.J., Miller, M.L., Bloom, J.A., Fridrich, J., Kalker, T.: Digital Watermarking and Steganography. Morgan Kaufmann, Burlington (2008)Google Scholar
  7. 7.
    Domingo-Ferrer, J.: Anonymous fingerprinting of electronic information with automatic identification of redistributors. Electron. Lett. 34(13), 1303–1304 (1998)CrossRefGoogle Scholar
  8. 8.
    Domingo-Ferrer, J.: Anonymous fingerprinting based on committed oblivious transfer. In: Public Key Cryptography-PKC 1999, LNCS, vol. 1560, pp. 43–52. Springer, Berlin (1999)Google Scholar
  9. 9.
    Domingo-Ferrer, J., Herrera-Joancomartí, J.: Short collusion-secure fingerprints based on dual binary Hamming codes. Electron. Lett. 36(20), 1697–1699 (2000)CrossRefGoogle Scholar
  10. 10.
    Domingo-Ferrer, J., Martínez, S., Sánchez, D., Soria-Comas, J.: Co-utility: self-enforcing protocols for the mutual benefit of participants. Eng. Appl. Artif. Intell. 59, 148–158 (2017)CrossRefGoogle Scholar
  11. 11.
    Domingo-Ferrer, J., Megías, D.: Distributed multicast of fingerprinted content based on a rational peer-to-peer community. Comput. Commun. 36, 542–550 (2013)CrossRefGoogle Scholar
  12. 12.
    Domingo-Ferrer, J., Sánchez, D., Soria-Comas, J.: Co-utility: self-enforcing collaborative protocols with mutual help. Prog. Artif. Intell. 5(2), 105–110 (2016)CrossRefGoogle Scholar
  13. 13.
    Fallahpour, M., Megías, D.: High capacity audio watermarking using the high frequency band of the wavelet domain. Multimed. Tools Appl. 52(2), 485–498 (2011)CrossRefGoogle Scholar
  14. 14.
    Fallahpour, M., Megías, D.: Secure logarithmic audio watermarking scheme based on the human auditory system. Multimed. Syst. 20, 155–164 (2014)CrossRefGoogle Scholar
  15. 15.
    Goldberg, D.: Genetic Algorithms in Search. Optimization and Machine Learning. Addison-Wesley, Boston (1989)zbMATHGoogle Scholar
  16. 16.
    Katzenbeisser, S., Lemma, A., Celik, M., van der Veen, M., Maas, M.: A buyer-seller watermarking protocol based on secure embedding. IEEE Trans. Inf. Forensics Secur. 3(4), 783–786 (2008)CrossRefGoogle Scholar
  17. 17.
    Kuribayashi, M.: On the implementation of spread spectrum fingerprinting in asymmetric cryptographic protocol. EURASIP J. Inf. Secur. 2010, art 694797 (2010)Google Scholar
  18. 18.
    Lei, C.-L., Yu, P.-L., Tsai, P.-L., Chan, M.-H.: An efficient and anonymous buyer-seller watermarking protocol. IEEE Trans. Image Process. 13(12), 1618–1626 (2004)CrossRefGoogle Scholar
  19. 19.
    Megías, D.: Improved privacy-preserving P2P multimedia distribution based on recombined fingerprints. IEEE Trans. Dependable Secur. Comput. 12(2), 179–189 (2015)CrossRefGoogle Scholar
  20. 20.
    Megías, D., Serra-Ruiz, J., Fallahpour, M.: Efficient self-synchronised blind audio watermarking system based on time domain and FFT amplitude modification. Signal Process. 90(12), 3078–3092 (2010)CrossRefzbMATHGoogle Scholar
  21. 21.
    Megías, D., Domingo-Ferrer, J.: DNA-inspired anonymous fingerprinting for efficient peer-to-peer content distribution. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2013), pp. 2376–2383 (2013)Google Scholar
  22. 22.
    Megías, D., Domingo-Ferrer, J.: Privacy-aware peer-to-peer content distribution using automatically recombined fingerprints. Multimed. Syst. 20(2), 105–125 (2014)CrossRefGoogle Scholar
  23. 23.
    Memon, N., Wong, P.-W.: A buyer-seller watermarking protocol. IEEE Trans. Image Process. 10(4), 643–649 (2001)CrossRefzbMATHGoogle Scholar
  24. 24.
    Nuida, K., Fujitsu, S., Hagiwara, M., Kitagawa, T., Watanabe, H, Ogawa, K., Imai, H.: An improvement of Tardos’s collusion-secure fingerprinting codes with very short lengths. In: Proceedings of the 17th International Conference on Applied Algebra, Algebraic Algorithms and Error-correcting Codes (AAECC’07), pp. 80–89. Springer, Berlin (2007)Google Scholar
  25. 25.
    Pfitzmann, B., Waidner, M.: Anonymous fingerprinting. In: Advances in Cryptology-EUROCRYPT’96, LNCS, vol. 1233, pp. 88–102. Springer, Berlin (1997)Google Scholar
  26. 26.
    Pfitzmann, B., Sadeghi, A.-R.: Coin-based anonymous fingerprinting. In: Advances in Cryptology-EUROCRYPT’99, LNCS, vol. 1592, pp. 150–164. Springer, Berlin (1999)Google Scholar
  27. 27.
    Preda, R.O., Vizireanu, D.N.: Robust wavelet-based video watermarking scheme for copyright protection using the human visual system. J. Electron. Imaging 20, 13022–130030 (2011)CrossRefGoogle Scholar
  28. 28.
    Prins, J.P., Erkin, Z., Lagendijk, R.L.: Anonymous fingerprinting with robust QIM watermarking techniques. EURASIP J. Inf. Secur. 2007, art 20 (2007)Google Scholar
  29. 29.
    Tardos, G.: Optimal probabilistic fingerprint codes. In: Proceedings of the 35th Annual ACM Symposium on Theory of Computing (STOC ’03), pp. 116–125. ACM, New York (2003)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Internet Interdisciplinary Institute (IN3), Universitat Oberta de CatalunyaCastelldefels, CataloniaSpain
  2. 2.UNESCO Chair in Data Privacy, Department of Computer Science and MathematicsUniversitat Rovira i VirgiliTarragona, CataloniaSpain

Personalised recommendations