Secure Multi-Party Computation of Boolean Circuits with Applications to Privacy in On-Line Marketplaces

  • Seung Geol Choi
  • Kyung-Wook Hwang
  • Jonathan Katz
  • Tal Malkin
  • Dan Rubenstein
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7178)

Abstract

Protocols for generic secure multi-party computation (MPC) generally come in two forms: they either represent the function being computed as a boolean circuit, or as an arithmetic circuit over a large field. Either type of protocol can be used for any function, but the choice of which protocol to use can have a significant impact on efficiency. The magnitude of the effect, however, has never been quantified.

With this in mind, we implement the MPC protocol of Goldreich, Micali, and Wigderson [13], which uses a boolean representation and is secure against a semi-honest adversary corrupting any number of parties. We then consider applications of secure MPC in on-line marketplaces, where customers select resources advertised by providers and it is desired to ensure privacy to the extent possible. Problems here are more naturally formulated in terms of boolean circuits, and we study the performance of our MPC implementation relative to existing ones that use an arithmetic-circuit representation. Our protocol easily handles tens of customers/providers and thousands of resources, and outperforms existing implementations including FairplayMP [3], VIFF [11], and SEPIA [7].

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D.A., Rabkin, A., Stoica, I., Zaharia, M.: Above the clouds: A Berkeley view of cloud computing. Technical Report UCB/EECS-2009-28, EECS Department, UC Berkeley (2009)Google Scholar
  2. 2.
    Beaver, D.: Precomputing Oblivious Transfer. In: Coppersmith, D. (ed.) CRYPTO 1995. LNCS, vol. 963, pp. 97–109. Springer, Heidelberg (1995)Google Scholar
  3. 3.
    Ben-David, A., Nisan, N., Pinkas, B.: FairplayMP: A system for secure multi-party computation. In: 15th ACM Conf. on Computer and Communications Security, pp. 257–266. ACM Press (2008)Google Scholar
  4. 4.
    Bogdanov, D., Laur, S., Willemson, J.: Sharemind: A Framework for Fast Privacy-Preserving Computations. In: Jajodia, S., Lopez, J. (eds.) ESORICS 2008. LNCS, vol. 5283, pp. 192–206. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Bogetoft, P., Christensen, D.L., Damgård, I., Geisler, M., Jakobsen, T., Krøigaard, M., Nielsen, J.D., Nielsen, J.B., Nielsen, K., Pagter, J., Schwartzbach, M., Toft, T.: Secure Multiparty Computation Goes Live. In: Dingledine, R., Golle, P. (eds.) FC 2009. LNCS, vol. 5628, pp. 325–343. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  6. 6.
    Bogetoft, P., Damgård, I., Jakobsen, T., Nielsen, K., Pagter, J., Toft, T.: A Practical Implementation of Secure Auctions Based on Multiparty Integer Computation. In: Di Crescenzo, G., Rubin, A. (eds.) FC 2006. LNCS, vol. 4107, pp. 142–147. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  7. 7.
    Burkhart, M., Strasser, M., Many, D., Dimitropoulos, X.: SEPIA: Privacy-preserving aggregation of multi-domain network events and statistics. In: 19th USENIX Security Symposium, pp. 223–240. USENIX Association (2010)Google Scholar
  8. 8.
    Buyya, R., Abramson, D., Venugopal, S.: The grid economy. Proc. IEEE 93(3), 698–714 (2005)CrossRefGoogle Scholar
  9. 9.
    Chen, Y., Katz, R.H., Katz, Y.H., Kubiatowicz, J.D.: Dynamic Replica Placement for Scalable Content Delivery. In: Druschel, P., Kaashoek, M.F., Rowstron, A. (eds.) IPTPS 2002. LNCS, vol. 2429, pp. 306–318. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  10. 10.
    Choi, S.G., Hwang, K., Katz, J., Malkin, T., Rubenstein, D.: Secure multi-party computation of boolean circuits with applications to privacy in on-line marketplaces. Cryptology ePrint Archive, Report 2011/257 (2011), http://eprint.iacr.org/2011/257
  11. 11.
    Damgård, I., Geisler, M., Krøigaard, M., Nielsen, J.B.: Asynchronous Multiparty Computation: Theory and Implementation. In: Jarecki, S., Tsudik, G. (eds.) PKC 2009. LNCS, vol. 5443, pp. 160–179. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  12. 12.
    Goldreich, O.: Foundations of Cryptography. Basic Applications, vol. 2. Cambridge University Press, Cambridge (2004)CrossRefMATHGoogle Scholar
  13. 13.
    Goldreich, O., Micali, S., Wigderson, A.: How to play any mental game, or a completeness theorem for protocols with honest majority. In: 19th ACM STOC Annual ACM Symposium on Theory of Computing (STOC), pp. 218–229. ACM Press (1987)Google Scholar
  14. 14.
    Henecka, W., Kögl, S., Sadeghi, A.-R., Schneider, T., Wehrenberg, I.: TASTY: Tool for automating secure two-party computations. In: 17th ACM Conf. on Computer and Communications Security (CCCS), pp. 451–462. ACM Press (2010)Google Scholar
  15. 15.
    Huang, Y., Evans, D., Katz, J., Malka, L.: Faster secure two-party computation using garbled circuits. In: 20th USENIX Security Symposium. USENIX Association (2011)Google Scholar
  16. 16.
    Ishai, Y., Kilian, J., Nissim, K., Petrank, E.: Extending Oblivious Transfers Efficiently. In: Boneh, D. (ed.) CRYPTO 2003. LNCS, vol. 2729, pp. 145–161. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  17. 17.
    Jakobsen, T.P., Makkes, M.X., Nielsen, J.D.: Efficient Implementation of the Orlandi Protocol. In: Zhou, J., Yung, M. (eds.) ACNS 2010. LNCS, vol. 6123, pp. 255–272. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  18. 18.
    Kangasharju, J., Roberts, J., Ross, K.W.: Object replication strategies in content distribution networks. Computer Communications 25(4), 376–383 (2002)CrossRefGoogle Scholar
  19. 19.
    Kolesnikov, V., Sadeghi, A.-R., Schneider, T.: Improved Garbled Circuit Building Blocks and Applications to Auctions and Computing Minima. In: Garay, J.A., Miyaji, A., Otsuka, A. (eds.) CANS 2009. LNCS, vol. 5888, pp. 1–20. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  20. 20.
    Lewis, P.R., Marrow, P., Yao, X.: Evolutionary Market Agents for Resource Allocation in Decentralised Systems. In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN 2008. LNCS, vol. 5199, pp. 1071–1080. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  21. 21.
    Li, B., Li, H., Xu, G., Xu, H.: Efficient reduction of 1-out-of-n oblivious transfers in random oracle model. Cryptology ePrint Archive, Report 2005/279 (2005)Google Scholar
  22. 22.
    Lindell, Y., Pinkas, B., Smart, N.P.: Implementing Two-Party Computation Efficiently with Security against Malicious Adversaries. In: Ostrovsky, R., De Prisco, R., Visconti, I. (eds.) SCN 2008. LNCS, vol. 5229, pp. 2–20. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  23. 23.
    Malka, L., Katz, J.: VMCrypt — modular software architecture for scalable secure computation, http://eprint.iacr.org/2010/584
  24. 24.
    Malkhi, D., Nisan, N., Pinkas, B., Sella, Y.: Fairplay — a secure two-party computation system. In: 13th USENIX Security Symposium, pp. 287–302. USENIX Association (2004)Google Scholar
  25. 25.
    Naor, M., Pinkas, B.: Computationally secure oblivious transfer. J. Cryptology 18(1), 1–35 (2005)MathSciNetCrossRefMATHGoogle Scholar
  26. 26.
    Pinkas, B., Schneider, T., Smart, N.P., Williams, S.C.: Secure Two-Party Computation is Practical. In: Matsui, M. (ed.) ASIACRYPT 2009. LNCS, vol. 5912, pp. 250–267. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  27. 27.
    Schnizler, B., Neumann, D., Veit, D., Weinhardt, C.: Trading grid services — a multi-attribute combinatorial approach. European J. Operational Research 187(3), 943–961 (2008)CrossRefMATHGoogle Scholar
  28. 28.
    Tan, Z., Gurd, J.R.: Market-based grid resource allocation using a stable continuous double auction. In: Proc. 8th IEEE/ACM Intl. Conf. on Grid Computing, pp. 283–290. IEEE (2007)Google Scholar
  29. 29.
    Wolski, R., Plank, J.S., Brevik, J., Bryan, T.: Analyzing market-based resource allocation strategies for the computational grid. International Journal of High Performance Computing Applications 15(3), 258–281 (2006)CrossRefGoogle Scholar
  30. 30.
    Yao, A.C.-C.: How to generate and exchange secrets. In: 27th Annual Symp. on Foundations of Computer Science (FOCS), pp. 162–167. IEEE (1986)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Seung Geol Choi
    • 1
  • Kyung-Wook Hwang
    • 2
  • Jonathan Katz
    • 1
  • Tal Malkin
    • 2
  • Dan Rubenstein
    • 2
  1. 1.University of MarylandUS
  2. 2.Columbia UniversityUS

Personalised recommendations