MPC for MPC: Secure Computation on a Massively Parallel Computing Architecture.

Ronald Cramer, Ivan Damgård, Jesper Buus Nielsen

Zhifang Zhang, Mulan Liu, Liangliang Xiao

Abstract. As an extension of multi-party computation (MPC), we propose the concept of secure parallel multi-party computation which is to securely compute multi-functions against an adversary with multistructures. Precisely, there are m functions f1,..., fm and m adversary structures A1,..., Am, where fi is required to be securely computed against an Ai-adversary. We give a general construction to build a parallel multi-party computation protocol from any linear multi-secret sharing scheme (LMSSS), provided that the access structures of the LMSSS allow MPC at all. When computing complicated functions, our protocol has more advantage in communication complexity than the “direct sum” method which actually executes a MPC protocol for each function. The paper also provides an efficient and generic construction to obtain from any LMSSS a multiplicative LMSSS for the same multi-access structure. 1

Zuzana Beerliová-Trubíniová, Martin Hirt

Donghang Lu, Albert Yu, Aniket Kate +1 more

While the practicality of secure multi-party computation (MPC) has been extensively analyzed and improved over the past decade, we are hitting the limits of efficiency with the traditional approaches of representing the computed functionalities as generic arithmetic or Boolean circuits. This work follows the design principle of identifying and constructing fast and provably-secure MPC protocols to evaluate useful high-level algebraic abstractions; thus, improving the efficiency of all applications relying on them. We present Polymath, a constant-round secure computation protocol suite for the secure evaluation of (multi-variate) polynomials of scalars and matrices, functionalities essential to numerous data-processing applications. Using precise natural precomputation and high-degree of parallelism prevalent in the modern computing environments, Polymath can make latency of secure polynomial evaluations of scalars and matrices independent of polynomial degree and matrix dimensions.

Yehuda Lindell

MPC has moved from theoretical study to real-world usage. How is it doing?

Michele Ciampi, Divya Ravi, Luisa Siniscalchi +1 more

Secure multi-party computation (MPC) protocols that are resilient to a dishonest majority allow the adversary to get the output of the computation while, at the same time, forcing the honest parties to abort. Aumann and Lindell introduced the enhanced notion of security with identifiable abort , which still allows the adversary to trigger an abort but, at the same time, it enables the honest parties to agree on the identity of the party that led to the abort. More recently, in Eurocrypt 2016, Garg et al. showed that, assuming access to a simultaneous message exchange channel for all the parties, at least four rounds of communication are required to securely realize non-trivial functionalities in the plain model. Following Garg et al., a sequence of works has matched this lower bound, but none of them achieved security with identifiable abort. In this work, we close this gap and show that four rounds of communication are also sufficient to securely realize any functionality with identifiable abort using standard and generic polynomial-time assumptions. To achieve this result we introduce the new notion of bounded-rewind secure MPC that guarantees security even against an adversary that performs a mild form of reset attacks. We show how to instantiate this primitive starting from any MPC protocol and by assuming trapdoor-permutations. The notion of bounded-rewind secure MPC allows for easier parallel composition of MPC protocols with other (interactive) cryptographic primitives. Therefore, we believe that this primitive can be useful in other contexts in which it is crucial to combine multiple primitives with MPC protocols while keeping the round complexity of the final protocol low.