Circuit-Free General-Purpose Multi-Party Computation via Co-Utile Unlinkable Outsourcing

TL;DR

This paper introduces a circuit-free, privacy-preserving multi-party computation method that leverages anonymous outsourcing and reputation systems, enabling arbitrary code execution without circuit translation and tolerating rational malicious participants.

Contribution

It presents a novel approach for MPC that avoids circuit translation, uses co-utile outsourcing with reputation, and works against rational malicious peers, simplifying implementation and enhancing privacy.

Findings

Reputation effectively captures peer behavior.

The approach ensures correct results for high-reputation parties.

Method supports arbitrary code without circuit translation.

Abstract

Multiparty computation (MPC) consists in several parties engaging in joint computation in such a way that each party's input and output remain private to that party. Whereas MPC protocols for specific computations have existed since the 1980s, only recently general-purpose compilers have been developed to allow MPC on arbitrary functions. Yet, using today's MPC compilers requires substantial programming effort and skill on the user's side, among other things because nearly all compilers translate the code of the computation into a Boolean or arithmetic circuit. In particular, the circuit representation requires unrolling loops and recursive calls, which forces programmers to (often manually) define loop bounds and hardly use recursion. We present an approach allowing MPC on an arbitrary computation expressed as ordinary code with all functionalities that does not need to be translated into a circuit. Our notion of input and output privacy is predicated on unlinkability. Our method leverages co-utile computation outsourcing using anonymous channels via decentralized reputation, makes a minimalistic use of cryptography and does not require participants to be honest-but-curious: it works as long as participants are rational (self-interested), which may include rationally malicious peers (who become attackers if this is advantageous to them). We present example applications, including e-voting. Our empirical work shows that reputation captures well the behavior of peers and ensures that parties with high reputation obtain correct results.