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Computer Standards & Interfaces

Efficient maliciously secure two-party mixed-protocol framework for data-driven computation tasks

Yulin Wu, Xuan Wang, Willy Susilo, Guomin Yang, Zoe L. Jiang, Hao Wang, Tong Wu

Published Aug 24, 2021• 4 citations
Publisher
DOI
10.1016/j.csi.2021.103571

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Secure two-party computation is always the focus in the international cryptographic community, and establishing a secure two-party computation for determining the equality of data is a fundamental and crucial task within this field.There is still substantial room for improvement in terms of efficiency and security, so it is worth exploring further.In this paper, two theorems are proved from camera imaging of straight lines on a flat surface and the equality judgement of data between the two-party is innovatively converted into judging whether the inner products of the vectors owned by the two parties are zeroes.Based on the specific property of these vectors, a security protocol is established to determine whether those inner products are zeroes, which realizes the protocol scheme of judging the data equality of two-party under the semi-honest model and analyses its security theoretically.The scheme needs key stream for dynamic data encoding, since only basic arithmetic operations (integer addition, subtraction and multiplication) and a final modulus operation are required after encode without high-order and decimal operations, and the communication complexity is O(1), which greatly improves the efficiency.This scheme may not fit for malicious model, we could use the existing agreements of malicious model to determine whether those inner products are zeroes, by the conversion in this paper we also could complete the equality judgement.
In this thesis we design and implement three approaches to provide efficient Secure Two- Party Computation (2PC) protocols that are secure in presence of malicious adversaries. The field of secure two-party computation enables two mutually distrusting parties, each with their own private input, to run a computation of an arbitrary program. At the end of the computation, nothing about their private input is leaked except for what can be learned from the output of the computation. The seminal work of Yao in 1986 provided the first proof that such a computation is feasible using the so called garbled circuits and given an Oblivious Transfer protocol. In this thesis, we follow Yao’s garbled circuit approach and focus on efficient protocols that are secure against malicious adversaries. We examine three different categories of optimization. In each category, we present a 2PC protocol, prove its security, and implement it as a proof of concept to demonstrate its running time in practice. Non-interactive Secure Computation: In this category, we offer the first implementation of a malicious 2PC protocol that reduces the required rounds of interaction between the two parties to only two rounds (i.e., each party sends only one message to the other party). Mixed Secure Two-Party Computation: In the second category we target big and complex programs and break them into subprograms. Then, we compute each subprogram using the most efficient 2PC protocol that is suitable for it. Finally, we securely connect these subprograms together. The goal is to reduce the overhead of the garbled circuits significantly, which results in a more efficient overall 2PC protocol for programs with specific properties. Secure Computation for Random Access Machine Programs: In the third category, we target programs that require random access to the memory (as opposed to a sequential access). We present the first efficient maliciously-secure protocol for computing such programs.