Cheater Identification on a Budget: MPC with Identifiable Abort from Pairwise MACs

Carsten Baum, Nikolas Melissaris, Rahul Rachuri, Peter Scholl

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cheater identification in secure multi-party computation (MPC) allows the honest parties to agree upon the identity of a cheating party, in case the protocol aborts. In the context of a dishonest majority, this becomes especially critical, as it serves to thwart denial-of-service attacks and mitigate known impossibility results on ensuring fairness and guaranteed output delivery. In this work, we present a new, lightweight approach to achieving identifiable abort in dishonest majority MPC. We avoid all of the heavy machinery used in previous works, instead relying on a careful combination of lightweight detection mechanisms and techniques from state-of-the-art protocols secure with (non-identifiable) abort. At the core of our construction is a homomorphic, multi-receiver commitment scheme secure with identifiable abort. This commitment scheme can be constructed from cheap vector oblivious linear evaluation protocols based on learning parity with noise. To support cheater identification, we design a general compilation technique, similar to a compiler of Ishai et al. (Crypto 2014), but avoid its requirement for adaptive security of the underlying protocol. Instead, we rely on a different (and seemingly easier to achieve) property we call online extractability, which may be of independent interest. Our MPC protocol can be viewed as a version of the BDOZ MPC scheme (Bendlin et al., Eurocrypt 2011) based on pairwise information-theoretic MACs, enhanced to support cheater identification and a highly efficient preprocessing phase, essentially as efficient as the non-identifiable protocol of Le Mans (Rachuri & Scholl, Crypto 2022).

Original languageEnglish
Title of host publicationAdvances in Cryptology – CRYPTO 2024 - 44th Annual International Cryptology Conference, Proceedings
EditorsLeonid Reyzin, Douglas Stebila
PublisherSpringer Science and Business Media Deutschland GmbH
Pages454-488
Number of pages35
ISBN (Print)9783031683961
DOIs
StatePublished - 2024
Externally publishedYes
Event44th Annual International Cryptology Conference, CRYPTO 2024 - Santa Barbara, United States
Duration: 18 Aug 202422 Aug 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14927 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference44th Annual International Cryptology Conference, CRYPTO 2024
Country/TerritoryUnited States
CitySanta Barbara
Period18/08/2422/08/24

Bibliographical note

Publisher Copyright:
© International Association for Cryptologic Research 2024.

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