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A brief history of practical multi-party computation

Nigel Paul Smart

Published Nov 4, 2013• 0 citations
Publisher

Abstract

In the last few years amazing progress has been made in turning the theoretical area of cryptography called Multi-Party Computation into a practical reality. In particular we can now use MPC to solve many security tasks which were thought impossible just a few years ago. In this talk I will overview this progress, and examine how far we have come in such a short space of time.

DOI
10.1145/2517872.2517880

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In the last few years amazing progress has been made in turning the theoretical area of cryptography called Multi-Party Computation into a practical reality. In particular we can now use MPC to solve many security tasks which were thought impossible just a few years ago. In this talk I will overview this progress, and examine how far we have come in such a short space of time.
Secure multi-party computation (MPC) has evolved from a theoretical curiosity in the 1980s to a tool for building real systems today. Over the past decade, MPC has been one of the most active research areas in both theoretical and applied cryptography. This article introduces several important MPC protocols, and surveys methods for improving the efficiency of privacy-preserving applications built using MPC. Besides giving a broad overview of the field and the insights of the main constructions, we overview the most currently active areas of MPC research and aim to give readers insights into what problems are practically solvable using MPC today and how different threat models and assumptions impact the practicality of different approaches.
The aim of this paper is to present some of the recent progress in efficient secure multiparty computation (MPC). In MPC we have a set of parties owning a set of private inputs. The par ties want to compute a function of their inputs, but they do not trust each other, therefore they need a cryptographic protocol to perform the computation in a way that 1) the output is correct and 2) cheating parties will not be able to learn any information about the honest parties inputs. Even though this problem has been formulated and essentially solved almost 30 years ago, practical solutions that can be relevant for real-world applications have been discovered only in the last few years. We will present some of these advances, trying to explain to a non-specialized audience the significance of the several existing security notions.
In 1982, Yao presented a protocol that allowed two parties to compute over their private inputs while revealing nothing but the final output. This first theoretical construction originated a fruitful line of research exploring the possibilities of the cryptographic technique known as multi-party computation, or MPC. Today, we have MPC schemes with practical efficiency that can be used for a wide range of applications and use cases, from securing cryptographic keys to training Machine Learning models on private data. Despite the advancements from the past few decades, we have only started to bridge the gap between theory and practice, and several obstacles stand in the way of the widespread adoption of MPC. First, the performance overhead depends heavily on the computation we want to perform. Not all computations are well-suited to be distributed with MPC, and algorithms must usually be refactored before they can be executed securely. Furthermore, the practical efficiency of most modern protocols quickly deteriorates as the number of parties increases and comes at the expense of the security guarantees provided. On the other hand, almost all academic works assume a static set of MPC parties, all pairwise connected by dedicated channels in a network without delays or failures. Yet, these assumptions are hardly achievable in current real-world networks. In this thesis, we study three practical aspects of multi-party computation: (i) we discuss how to improve performance by designing algorithms tailor-made for execution with MPC. To this end, we present and evaluate secure auction mechanisms for the financial setting and for the peer-to-peer electricity market. (ii) We analyse the information leakage from the MPC computation outputs. In particular, we focus on the case of individual and private correlated outputs, for which we propose a new privacy notion. Lastly, (iii) we consider the problem of building efficient large-scale MPC. We explore the possibilities and limitations associated with standard (fully connected) networks and present a new protocol with a star-like network topology and resilience against delayed parties.
A central goal of cryptography is Secure Multi-party Computation (MPC), where n parties desire to compute a function of their joint inputs without letting any party learn about the inputs of its peers. Unfortunately, it is well-known that MPC guaranteeing output delivery to every party is infeasible when a majority of the parties are malicious. In fact, parties operating over a point-to-point network (i.e., without access to a broadcast channel) cannot even reach an agreement on the output when more than one third of the parties are malicious (Lamport, Shostak, and Pease, JACM 1980).
Abstract. In this note, we report on the first large-scale and practical application of multiparty computation, which took place in January 2008. We also report on the novel cryptographic protocols that were used. 1 Introduction and History In multiparty computation (MPC), we consider a number of players P1,..., Pn, who initially each hold inputs x1,..., xn, and we then want to securely compute some function f on these inputs, where f(x1,..., xn) = (y1,..., yn), such that Pi learns yi but no other information. This should hold, even if players exhibit some amount of adversarial behavior. The goal can be accomplished by an interactive