Secure Multiparty Computation with Partial Fairness
Amos Beimel, Eran Omri, and Ilan Orlov

TL;DR
This paper develops protocols for multiparty secure computation with partial fairness, extending previous two-party results to multiple parties with certain restrictions, and identifies fundamental limitations for larger numbers of parties.
Contribution
It introduces 1/p-secure multiparty protocols for constant parties with less than 2/3 corruption, under specific conditions on functionality size and randomness.
Findings
Protocols work for constant number of parties with less than 2/3 corruptions.
Efficiency achieved for deterministic functions with polynomial domain size and constant domain size.
Impossibility results for super-constant parties with polynomial domain size.
Abstract
A protocol for computing a functionality is secure if an adversary in this protocol cannot cause more harm than in an ideal computation where parties give their inputs to a trusted party which returns the output of the functionality to all parties. In particular, in the ideal model such computation is fair -- all parties get the output. Cleve (STOC 1986) proved that, in general, fairness is not possible without an honest majority. To overcome this impossibility, Gordon and Katz (Eurocrypt 2010) suggested a relaxed definition -- 1/p-secure computation -- which guarantees partial fairness. For two parties, they construct 1/p-secure protocols for functionalities for which the size of either their domain or their range is polynomial (in the security parameter). Gordon and Katz ask whether their results can be extended to multiparty protocols. We study 1/p-secure protocols in the…
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Taxonomy
TopicsCryptography and Data Security · Complexity and Algorithms in Graphs · Privacy-Preserving Technologies in Data
