Communication Optimal Tardos-Based Asymmetric Fingerprinting

  • Aggelos Kiayias
  • Nikos Leonardos
  • Helger Lipmaa
  • Kateryna Pavlyk
  • Qiang Tang
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9048)

Abstract

Asymmetric fingerprinting schemes — introduced by Pfitzmann and Schunter in Eurocrypt 1996 — enable the transmission of a file stored in a server to a set of users so that each user obtains a variation of the file. The security considerations of these schemes are as follows: if any (appropriately bounded) subset of users collude to produce a “pirate” copy of the file, it is always possible for the server to prove to a third party judge the implication of at least one of them, while a malicious server can never implicate innocent users.

Given that asymmetric fingerprinting is supposed to distribute files of substantial size (e.g., media files including video and audio) any communication rate (defined as the size of the file over the total transmission length) less than 1 would render them practically useless. The existence of such schemes is currently open. Building on a rate close to 1 oblivious transfer (constructed from recently proposed rate optimal homomorphic encryption), we present the first asymmetric fingerprinting scheme that is communication optimal, i.e., its communication rate is arbitrarily close to 1 (for sufficiently large files) thus resolving this open question. Our scheme is based on Tardos codes, and we prove our scheme secure in an extended formal security model where we also deal with the important but previously unnoticed (in the context of asymmetric fingerprinting) security considerations of accusation withdrawal and adversarial aborts.

Keywords

Asymmetric fingerprinting Tardos Code Rate optimal Group accusation 
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References

  1. 1.
    Ambainis, A., Jakobsson, M., Lipmaa, H.: Cryptographic Randomized Response Techniques. In: Bao, F., Deng, R., Zhou, J. (eds.) PKC 2004. LNCS, vol. 2947, pp. 425–438. Springer, Heidelberg (2004) CrossRefGoogle Scholar
  2. 2.
    Amiri, E., Tardos, G.: High Rate Fingerprinting Codes And the Fingerprinting Capacity. In: Mathieu, C. (ed.) SODA 2009, pp. 336–345. SIAM, New York, January 4–6 (2009)Google Scholar
  3. 3.
    Blake, I.F., Kolesnikov, V.: Strong Conditional Oblivious Transfer and Computing on Intervals. In: Lee, P.J. (ed.) ASIACRYPT 2004. LNCS, vol. 3329, pp. 515–529. Springer, Heidelberg (2004) CrossRefGoogle Scholar
  4. 4.
    Boneh, D., Shaw, J.: Collusion-Secure Fingerprinting for Digital Data. In: Coppersmith, D. (ed.) CRYPTO 1995. LNCS, vol. 963, pp. 452–465. Springer, Heidelberg (1995) Google Scholar
  5. 5.
    Canetti, R.: Security and composition of multiparty cryptographic protocols. J. Cryptology 13(1), 143–202 (2000)CrossRefMATHMathSciNetGoogle Scholar
  6. 6.
    Charpentier, A., Fontaine, C., Furon, T., Cox, I.: An asymmetric fingerprinting scheme based on tardos codes. In: Proceedings of the 13th International Conference on Information Hiding, IH 2011, pp. 43–58 (2011)Google Scholar
  7. 7.
    Cleve, R., Limits on the security of coin flips when half the processors are faulty (extended abstract). In: STOC, pp. 364–369 (1986)Google Scholar
  8. 8.
    Damgård, I., Faust, S., Hazay, C.: Secure Two-Party Computation with Low Communication. In: Cramer, R. (ed.) TCC 2012. LNCS, vol. 7194, pp. 54–74. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  9. 9.
    Damgård, I., Jurik, M.: A generalisation, a simplification and some applications of paillier’s probabilistic public-key system. In: Public Key Cryptography, pp. 119–136 (2001)Google Scholar
  10. 10.
    Damgård, I., Zakarias, S.: Constant-Overhead Secure Computation of Boolean Circuits using Preprocessing. In: Sahai, A. (ed.) TCC 2013. LNCS, vol. 7785, pp. 621–641. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  11. 11.
    Dodis, Y., Halevi, S., Rabin, T.: A Cryptographic Solution to a Game Theoretic Problem. In: Bellare, M. (ed.) CRYPTO 2000. LNCS, vol. 1880, pp. 112–130. Springer, Heidelberg (2000) CrossRefGoogle Scholar
  12. 12.
    Fischlin, M.: A Cost-Effective Pay-Per-Multiplication Comparison Method for Millionaires. In: Naccache, D. (ed.) CT-RSA 2001. LNCS, vol. 2020, pp. 457–472. Springer, Heidelberg (2001) CrossRefGoogle Scholar
  13. 13.
    Goldreich, O.: The Foundations of Cryptography, vol. 2, Basic Applications. Cambridge University Press (2004)Google Scholar
  14. 14.
    Ishai, Y., Kushilevitz, E., Meldgaard, S., Orlandi, C., Paskin-Cherniavsky, A.: On the Power of Correlated Randomness in Secure Computation. In: Sahai, A. (ed.) TCC 2013. LNCS, vol. 7785, pp. 600–620. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  15. 15.
    Ishai, Y., Paskin, A.: Evaluating Branching Programs on Encrypted Data. In: Vadhan, S.P. (ed.) TCC 2007. LNCS, vol. 4392, pp. 575–594. Springer, Heidelberg (2007) CrossRefGoogle Scholar
  16. 16.
    Kiayias, A., Leonardos, N., Lipmaa, H., Pavlyk, K., Tang, Q.: Near Optimal Rate Homomorphic Encryption for Branching Programs. Technical Report 2014 (2014). http://eprint.iacr.org/2014/851
  17. 17.
    Kiayias, A., Pehlivanoglu, S.: Encryption for Digital Content, vol. 52. Advances in Information Security. Springer, US (October 2010)Google Scholar
  18. 18.
    Laur, S., Lipmaa, H.: A New Protocol for Conditional Disclosure of Secrets and Its Applications. In: Katz, J., Yung, M. (eds.) ACNS 2007. LNCS, vol. 4521, pp. 207–225. Springer, Heidelberg (2007) CrossRefGoogle Scholar
  19. 19.
    Lipmaa, H.: First CPIR Protocol with Data-Dependent Computation. In: Lee, D., Hong, S. (eds.) ICISC 2009. LNCS, vol. 5984, pp. 193–210. Springer, Heidelberg (2010) CrossRefGoogle Scholar
  20. 20.
    Naor, M., Nissim, K.: Communication preserving protocols for secure function evaluation. In: STOC, pp. 590–599 (2001)Google Scholar
  21. 21.
    Pfitzmann, B.: Trials of traced traitors. In: Information Hiding, pp. 49–64 (1996)Google Scholar
  22. 22.
    Pfitzmann, B., Schunter, M.: Asymmetric Fingerprinting. In: Maurer, U.M. (ed.) EUROCRYPT 1996. LNCS, vol. 1070, pp. 84–95. Springer, Heidelberg (1996) CrossRefGoogle Scholar
  23. 23.
    Pfitzmann, B., Waidner, M.: Asymmetric fingerprinting for larger collusions. In: ACM Conference on Computer and Communications Security, pp. 151–160 (1997)Google Scholar
  24. 24.
    Rial, A., Balasch, J., Preneel, B.: A privacy-preserving buyer-seller watermarking protocol based on priced oblivious transfer. IEEE Transactions on Information Forensics and Security 6(1), 202–212 (2011)CrossRefGoogle Scholar
  25. 25.
    Rial, A., Deng, M., Bianchi, T., Piva, A., Preneel, B.: A provably secure anonymous buyer-seller watermarking protocol. IEEE Transactions on Information Forensics and Security 5(4), 920–931 (2010)CrossRefGoogle Scholar
  26. 26.
    Tardos, G.: Optimal probabilistic fingerprint codes. J. ACM 55(2) (2008)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Aggelos Kiayias
    • 1
  • Nikos Leonardos
    • 2
  • Helger Lipmaa
    • 3
  • Kateryna Pavlyk
    • 3
  • Qiang Tang
    • 1
    • 4
  1. 1.National and Kapodistrian University of AthensAthensGreece
  2. 2.Université Paris Diderot – Paris 7ParisFrance
  3. 3.University of TartuTartuEstonia
  4. 4.University of ConnecticutStorrsUSA

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