IACR News item: 19 April 2021
Gabrielle Beck, Aarushi Goel, Abhishek Jain, Gabriel Kaptchuk
ePrint Report
Running secure multiparty computation (MPC) protocols with hundreds or thousands of players would allow leveraging large volunteer networks (such as blockchains and Tor) and help justify honest majority assumptions. However, most existing protocols have at least a linear (multiplicative)dependence on the number of players, making scaling difficult. Known protocols with asymptotic efficiency independent of the number of parties (excluding additive factors) require expensive circuit transformations that induce large overheads.
We observe that the circuits used in many important applications of MPC such as training algorithms used to create machine learning models have a highly repetitive structure. We formalize this class of circuits and propose an MPC protocol that achieves O(|C|) total complexity for this class. We implement our protocol and show that it is practical and outperforms O(n|C|) protocols for modest numbers of players.
We observe that the circuits used in many important applications of MPC such as training algorithms used to create machine learning models have a highly repetitive structure. We formalize this class of circuits and propose an MPC protocol that achieves O(|C|) total complexity for this class. We implement our protocol and show that it is practical and outperforms O(n|C|) protocols for modest numbers of players.
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