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Authenticated Garbling and Efficient Maliciously Secure Two-Party Computation

Authors:

Samuel Ranellucci,

Jonathan KatzAuthors Info & Claims

CCS '17: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security

Pages 21 - 37

https://doi.org/10.1145/3133956.3134053

Published: 30 October 2017 Publication History

Abstract

We propose a simple and efficient framework for obtaining efficient constant-round protocols for maliciously secure two-party computation. Our framework uses a function-independent preprocessing phase to generate authenticated information for the two parties; this information is then used to construct a single "authenticated" garbled circuit which is transmitted and evaluated. We also show how to efficiently instantiate the preprocessing phase with a new, highly optimized version of the TinyOT protocol by Nielsen et al.

Our protocol outperforms existing work in both the single-execution and amortized settings, with or without preprocessing:

In the single-execution setting, our protocol evaluates an AES circuit with malicious security in 37 ms with an online time of 1 ms. Previous work with the best overall time requires 62 ms (with 14 ms online time); previous work with the best online time (also 1 ms) requires 124 ms overall.

If we amortize over 1024 executions, each AES computation requires just 6.7 ms with roughly the same online time as above. The best previous work in the amortized setting has roughly the same total time but does not support function-independent preprocessing.

Our work shows that the performance penalty for maliciously secure two-party computation (as compared to semi-honest security) is much smaller than previously believed.

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Index Terms

Authenticated Garbling and Efficient Maliciously Secure Two-Party Computation
1. Theory of computation
  1. Computational complexity and cryptography
    1. Cryptographic protocols

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cover image ACM Conferences

CCS '17: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security

October 2017

2682 pages

ISBN:9781450349468

DOI:10.1145/3133956

General Chair:
Bhavani Thuraisingham
The University of Texas at Dallas, USA
,
Program Chairs:
David Evans
University of Virginia
,
Tal Malkin
Columbia University
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Dongyan Xu
Purdue University

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Published: 30 October 2017

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CCS '17 Paper Acceptance Rate 151 of 836 submissions, 18%;

Overall Acceptance Rate 1,261 of 6,999 submissions, 18%

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Hashemi MForte DGanji F(2025)GuardianMPC: Backdoor-Resilient Neural Network ComputationIEEE Access10.1109/ACCESS.2025.352830413(11029-11048)Online publication date: 2025
https://doi.org/10.1109/ACCESS.2025.3528304
Li YXiao DLiu ZPang QWang S(2024)Metamorphic Testing of Secure Multi-party Computation (MPC) CompilersProceedings of the ACM on Software Engineering10.1145/36437811:FSE(1216-1237)Online publication date: 12-Jul-2024
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