MPC with Low Bottleneck-Complexity: Information-Theoretic Security and More

Authors Hannah Keller , Claudio Orlandi , Anat Paskin-Cherniavsky, Divya Ravi



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Author Details

Hannah Keller
  • Aarhus University, Denmark
Claudio Orlandi
  • Aarhus University, Denmark
Anat Paskin-Cherniavsky
  • Ariel University, Israel
Divya Ravi
  • Aarhus University, Denmark

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Hannah Keller, Claudio Orlandi, Anat Paskin-Cherniavsky, and Divya Ravi. MPC with Low Bottleneck-Complexity: Information-Theoretic Security and More. In 4th Conference on Information-Theoretic Cryptography (ITC 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 267, pp. 11:1-11:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/LIPIcs.ITC.2023.11

Abstract

The bottleneck-complexity (BC) of secure multiparty computation (MPC) protocols is a measure of the maximum number of bits which are sent and received by any party in protocol. As the name suggests, the goal of studying BC-efficient protocols is to increase overall efficiency by making sure that the workload in the protocol is somehow "amortized" by the protocol participants. Orlandi et al. [Orlandi et al., 2022] initiated the study of BC-efficient protocols from simple assumptions in the correlated randomness model and for semi-honest adversaries. In this work, we extend the study of [Orlandi et al., 2022] in two primary directions: (a) to a larger and more general class of functions and (b) to the information-theoretic setting. In particular, we offer semi-honest secure protocols for the useful function classes of abelian programs, "read-k" non-abelian programs, and "read-k" generalized formulas. Our constructions use a novel abstraction, called incremental function secret-sharing (IFSS), that can be instantiated with unconditional security or from one-way functions (with different efficiency trade-offs).

Subject Classification

ACM Subject Classification
  • Theory of computation → Cryptographic protocols
Keywords
  • Secure Multiparty Computation
  • Bottleneck Complexity
  • Information-theoretic

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