Garbled Circuits Reimagined: Logic Synthesis Unleashes Efficient Secure Computation
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Published:2023-11-23
Issue:4
Volume:7
Page:61
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ISSN:2410-387X
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Container-title:Cryptography
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language:en
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Short-container-title:Cryptography
Author:
Yu Mingfei1ORCID, Marakkalage Dewmini Sudara1ORCID, De Micheli Giovanni1
Affiliation:
1. Integrated System Laboratory, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
Abstract
Garbled circuit (GC) is one of the few promising protocols to realize general-purpose secure computation. The target computation is represented by a Boolean circuit that is subsequently transformed into a network of encrypted tables for execution. The need for distributing GCs among parties, however, requires excessive data communication, called garbling cost, which bottlenecks system performance. Due to the zero garbling cost of XOR operations, existing works reduce garbling cost by representing the target computation as the XOR-AND graph (XAG) with minimal structural multiplicative complexity (MC). Starting with a thorough study of the cipher-text efficiency of different types of logic primitives, for the first time, we propose XOR-OneHot graph (X1G) as a suitable logic representation for the generation of low-cost GCs. Our contribution includes (a) an exact algorithm to synthesize garbling-cost-optimal X1G implementations for small-scale functions and (b) a set of logic optimization algorithms customized for X1Gs, which together form a robust optimization flow that delivers high-quality X1Gs for practical functions. The effectiveness of the proposals is evidenced by comprehensive evaluations: compared with the state of the art, 7.34%, 26.14%, 13.51%, and 4.34% reductions in garbling costs are achieved on average for the involved benchmark suites, respectively, with reasonable runtime overheads.
Subject
Applied Mathematics,Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Software
Reference44 articles.
1. Bogetoft, P., Damgård, I., Jakobsen, T., Nielsen, K., Pagter, J., and Toft, T. (March, January 27). A Practical Implementation of Secure Auctions Based on Multiparty Integer Computation. Proceedings of the International Conference on Financial Cryptography and Data Security, Anguilla, British West Indies. 2. Clarkson, M.R., Chong, S., and Myers, A.C. (2008, January 18–22). Civitas: Toward a Secure Voting System. Proceedings of the IEEE Symposium on Security and Privacy, Oakland, CA, USA. 3. Gilad-Bachrach, R., Dowlin, N., Laine, K., Lauter, K., Naehrig, M., and Wernsing, J. (2016, January 19–24). CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy. Proceedings of the 33rd International Conference on International Conference on Machine Learning, New York, NY, USA. 4. Perfectly Secure and Efficient Two-Party Electronic-Health-Record Linkage;Chen;IEEE Internet Comput.,2018 5. Yao, A.C.C. (1986, January 27–29). How to Generate and Exchange Secrets. Proceedings of the 27th Annual Symposium on Foundations of Computer Science (SFCS 1986), Toronto, ON, Canada.
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