CMU-CS-22-118 Computer Science Department School of Computer Science, Carnegie Mellon University
Communication Complexity of Yifan Song Ph.D. Thesis July 2022
Since the notion of Multiparty Computation (MPC) was proposed three decades ago, a lot of research and effort has been done to improve the efficiency of MPC protocols. However, the inefficiency of the current state-of-the-art is still the major barrier that prevents MPC from being used more broadly. In this thesis, we study the communication complexity of information-theoretic MPC protocols.
Part I: Information Theoretic MPC with Honest Majority. In the setting of semi-honest security, we propose two improvements over the previously best-known result by Damgård and Nielsen (CRYPTO 2007). Our first protocol improves the communication complexity of the Damgård and Nielsen protocol from 6 field elements per party per gate to 4 elements. Our second protocol reduces the round complexity by a factor of 2 and achieves 4.5 field elements per party per gate. As for malicious security, we show that it can be achieved with the same concrete efficiency as the semi-honest security. Previously best known results have a factor of 2 in the communication complexity when compiling a semi-honest protocol to a maliciously secure one. Our result closes the communication efficiency gap between semi-honest security and malicious security (with abort).
Part II: Information-Theoretic MPC with Dishonest Majority in the Preprocessing Model. In this thesis, we construct the first MPC protocols in the preprocessing model for dishonest majority which achieves sub-linear amount of preprocessing data and communication complexity per gate in the number of parties n. To achieve our results, we extend the use of packed secret sharing to the dishonest majority setting. For a constant fraction of corrupted parties (i.e. if 99 percent of the parties are corrupt), we achieve O(1) field elements in both of the amount of preprocessing data and communication complexity per gate across all parties.
197 pages
Thesis Committee:
Srinivasan Seshan, Head, Computer Science Department
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