Welcome to the resource topic for 2023/1700
Title:
Scalable Mixed-Mode MPC
Authors: Radhika Garg, Kang Yang, Jonathan Katz, Xiao Wang
Abstract:Protocols for secure multi-party computation (MPC) supporting mixed-mode computation have found a lot of applications in recent years due to their flexibility in representing the function to be evaluated. However, existing mixed-mode MPC protocols are only practical for a small number of parties: they are either tailored to the case of two/three parties, or scale poorly for a large number of parties.
In this paper, we design and implement a new system for highly efficient and scalable mixed-mode MPC tolerating an arbitrary number of semi-honest corruptions. Our protocols allow secret data to be represented in Encrypted, Boolean, Arithmetic, or Yao form, and support efficient conversions between these representations.
- We design a multi-party table-lookup protocol, where both the index and the table can be kept private. The protocol is scalable even with hundreds of parties.
- Using the above protocol, we design efficient conversions between additive arithmetic secret sharings and Boolean secret sharings for a large number of parties. For 32 parties, our conversion protocols require 1184× to 8141× less communication compared to the state- of-the-art protocols MOTION and MP-SPDZ; this leads to up to 1275× improvement in running time under 1 Gbps network. The improvements are even larger with more parties.
- We also use new protocols to design an efficient multi-party distributed garbling protocol. The protocol could achieve asymptotically constant communication per party.
Our implementation will be made public.
ePrint: https://eprint.iacr.org/2023/1700
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