Cheater Detection in SPDZ Multiparty Computation

  • Gabriele SpiniEmail author
  • Serge Fehr
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10015)


In this work we revisit the SPDZ multiparty computation protocol by Damgård et al. for securely computing a function in the presence of an unbounded number of dishonest parties. The SPDZ protocol is distinguished by its fast performance. A downside of the SPDZ protocol is that one single dishonest party can enforce the computation to fail, meaning that the honest parties have to abort the computation without learning the outcome, whereas the cheating party may actually learn it. Furthermore, the dishonest party can launch such an attack without being identified to be the cheater. This is a serious obstacle for practical deployment: there are various reasons for why a party may want the computation to fail, and without cheater detection there is little incentive for such a party not to cheat. As such, in many cases, the protocol will actually fail to do its job.

In this work, we enhance the SPDZ protocol to allow for cheater detection: a dishonest party that enforces the protocol to fail will be identified as being the cheater. As a consequence, in typical real-life scenarios, parties will actually have little incentive to cheat, and if cheating still takes place, the cheater can be identified and discarded and the computation can possibly be re-done, until it succeeds.

The challenge lies in adding this cheater detection feature to the original protocol without increasing its complexity significantly. In case no cheating takes place, our new protocol is as efficient as the original SPDZ protocol which has no cheater detection. In case cheating does take place, there may be some additional overhead, which is still reasonable in size though, and since the cheater knows he will be caught, this is actually unlikely to occur in typical real-life scenarios.

Supplementary material


  1. 1.
    Baum, C., Orsini, E., Scholl, P.: Efficient secure multiparty computation with identifiable abort. IACR Cryptology ePrint Archive 2016:187 (2016)Google Scholar
  2. 2.
    Ben-Or, M., Goldwasser, S., Wigderson, A.: Completeness theorems for non-cryptographic fault-tolerant distributed computation. In: STOC 1988, pp. 1–10. ACM (1988)Google Scholar
  3. 3.
    Bendlin, R., Damgård, I., Orlandi, C., Zakarias, S.: Semi-homomorphic encryption and multiparty computation. In: Paterson, K.G. (ed.) EUROCRYPT 2011. LNCS, vol. 6632, pp. 169–188. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-20465-4_11 CrossRefGoogle Scholar
  4. 4.
    Canetti, R.: Universally composable security: a new paradigm for cryptographic protocols. In: FOCS 2001, pp. 136–145. IEEE Computer Society (2001)Google Scholar
  5. 5.
    Chaum, D., Crépeau, C., Damgard, I.: Multiparty unconditionally secure protocols. In: STOC 1988, pp. 11–19. ACM (1988)Google Scholar
  6. 6.
    Damgård, I., Keller, M., Larraia, E., Pastro, V., Scholl, P., Smart, N.P.: Practical covertly secure MPC for dishonest majority – or: breaking the SPDZ limits. In: Crampton, J., Jajodia, S., Mayes, K. (eds.) ESORICS 2013. LNCS, vol. 8134, pp. 1–18. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-40203-6_1 CrossRefGoogle Scholar
  7. 7.
    Damgård, I., Pastro, V., Smart, N., Zakarias, S.: Multiparty computation from somewhat homomorphic encryption. In: Safavi-Naini, R., Canetti, R. (eds.) CRYPTO 2012. LNCS, vol. 7417, pp. 643–662. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-32009-5_38 CrossRefGoogle Scholar
  8. 8.
    Goldreich, O., Micali, S., Wigderson, A.: How to play any mental game or a completeness theorem for protocols with honest majority. In: STOC 1987, pp. 218–229. ACM (1987)Google Scholar
  9. 9.
    Ishai, Y., Ostrovsky, R., Zikas, V.: Secure multi-party computation with identifiable abort. In: Garay, J.A., Gennaro, R. (eds.) CRYPTO 2014. LNCS, vol. 8617, pp. 369–386. Springer, Heidelberg (2014). doi: 10.1007/978-3-662-44381-1_21 CrossRefGoogle Scholar
  10. 10.
    Yao, A.C.: Protocols for secure computations. In: FOCS, pp. 160–164. IEEE Computer Society (1982)Google Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.CWI AmsterdamAmsterdamNetherlands
  2. 2.Mathematical InstituteLeiden UniversityLeidenNetherlands
  3. 3.Institut de Mathématiques de Bordeaux, UMR 5251, Université de BordeauxBordeauxFrance

Personalised recommendations