Annual International Conference on the Theory and Applications of Cryptographic Techniques

EUROCRYPT 2012: Advances in Cryptology – EUROCRYPT 2012 pp 483-501

Multiparty Computation with Low Communication, Computation and Interaction via Threshold FHE

  • Gilad Asharov
  • Abhishek Jain
  • Adriana López-Alt
  • Eran Tromer
  • Vinod Vaikuntanathan
  • Daniel Wichs
Conference paper

DOI: 10.1007/978-3-642-29011-4_29

Volume 7237 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Asharov G., Jain A., López-Alt A., Tromer E., Vaikuntanathan V., Wichs D. (2012) Multiparty Computation with Low Communication, Computation and Interaction via Threshold FHE. In: Pointcheval D., Johansson T. (eds) Advances in Cryptology – EUROCRYPT 2012. EUROCRYPT 2012. Lecture Notes in Computer Science, vol 7237. Springer, Berlin, Heidelberg

Abstract

Fully homomorphic encryption (FHE) enables secure computation over the encrypted data of a single party. We explore how to extend this to multiple parties, using threshold fully homomorphic encryption (TFHE). In such scheme, the parties jointly generate a common FHE public key along with a secret key that is shared among them; they can later cooperatively decrypt ciphertexts without learning anything but the plaintext. We show how to instantiate this approach efficiently, by extending the recent FHE schemes of Brakerski, Gentry and Vaikuntanathan (CRYPTO ’11, FOCS ’11, ITCS ’12) based on the (ring) learning with errors assumption. Our main tool is to exploit the property that such schemes are additively homomorphic over their keys.

Using TFHE, we construct simple multiparty computation protocols secure against fully malicious attackers, tolerating any number of corruptions, and providing security in the universal composability framework. Our protocols have the following properties: Low interaction: 3 rounds of interaction given a common random string, or 2 rounds with a public-key infrastructure. Low communication: independent of the function being computed (proportional to just input and output sizes). Cloud-assisted computation: the bulk of the computation can be efficiently outsourced to an external entity (e.g. a cloud service) so that the computation of all other parties is independent of the complexity of the evaluated function.

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Copyright information

© International Association for Cryptologic Research 2012

Authors and Affiliations

  • Gilad Asharov
    • 1
  • Abhishek Jain
    • 2
  • Adriana López-Alt
    • 3
  • Eran Tromer
    • 4
  • Vinod Vaikuntanathan
    • 5
  • Daniel Wichs
    • 6
  1. 1.Bar-Ilan UniversityUSA
  2. 2.University of California Los Angeles (UCLA)USA
  3. 3.New York University (NYU)USA
  4. 4.Tel Aviv UniversityIsrael
  5. 5.University of TorontoCanada
  6. 6.IBM Research, T.J. WatsonUSA