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IEEE Symposium on Reliable Distributed Systems (SRDS)

WINK:A Semi-Honest Secure Multi-Party Computation Framework with Efficient Comparison Protocol

Yuanqing Feng, Tao Bai, Zhi Gang Lu, Junjun Wu, Xueming Tang, Songfeng Lu

Published Sep 29, 2025• 0 citations
Publisher

Abstract

Secure multi-party computation (MPC) allows multiple parties to jointly compute a task while preserving the privacy of their individual inputs. In recent years, researchers have extensively studied various security protocols to improve the efficiency of MPC and reduce communication overhead. However, the efficiency of MPC in an$n$-party setting still remains a challenge. In this paper, we introduce WINK, a MPC framework designed for the semi-honest security model that accommodates an arbitrary number of participants. We design an$n$-party multiplication protocol in the$n$-out-of-$n$arithmetic secret sharing setting and, based on this, construct independent multiplication triples. We leverage a RLWE-based oblivious linear evaluation (OLE) technique to batch generate multiplication triples between any two parties, significantly reducing communication overhead. Furthermore, we design a constant-round n-party comparison protocol based on the properties of odd-sized rings and garbled circuits. This protocol completes in only three rounds of communication with the help of additional non-colluding semi-honest servers, marking a significant improvement over previous$n$-party comparison protocols. We prove that our framework achieves universally composable security. Moreover, experimental results demonstrate that our proposed comparison protocol outperforms existing comparison protocols in terms of efficiency.

DOI
10.1109/srds69199.2025.00047

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Secure multi-party computation (MPC) allows multiple parties to jointly compute a task while preserving the privacy of their individual inputs. In recent years, researchers have extensively studied various security protocols to improve the efficiency of MPC and reduce communication overhead. However, the efficiency of MPC in annnn-party setting still remains a challenge. In this paper, we introduce WINK, a MPC framework designed for the semi-honest security model that accommodates an arbitrary number of participants. We design annnn-party multiplication protocol in thennn-out-of-nnnarithmetic secret sharing setting and, based on this, construct independent multiplication triples. We leverage a RLWE-based oblivious linear evaluation (OLE) technique to batch generate multiplication triples between any two parties, significantly reducing communication overhead. Furthermore, we design a constant-round n-party comparison protocol based on the properties of odd-sized rings and garbled circuits. This protocol completes in only three rounds of communication with the help of additional non-colluding semi-honest servers, marking a significant improvement over previousnnn-party comparison protocols. We prove that our framework achieves universally composable security. Moreover, experimental results demonstrate that our proposed comparison protocol outperforms existing comparison protocols in terms of efficiency.
Secure multi-party computation (MPC) allows a set of parties to compute a function jointly while keeping their inputs private. Compared with the MPC based on garbled circuits, some recent research results show that MPC based on secret sharing (SS) works at a very high speed. Moreover, SS-based MPC can be easily vectorized and achieve higher throughput. In SS-based MPC, however, we need many communication rounds for computing concrete protocols like equality check, less-than comparison, etc. This property is not suited for large-latency environments like the Internet (or WAN). In this paper, we construct semi-honest secure communication-efficient two-party protocols. The core technique is Beaver triple extension, which is a new tool for treating multi-fan-in gates, and we also show how to use it efficiently. We mainly focus on reducing the number of communication rounds, and our protocols also succeed in reducing the number of communication bits (in most cases). As an example, we propose a less-than comparison protocol (under practical parameters) with three communication rounds. This is less than a half compared with the previous work. Moreover, the number of communication bits is also 38.4%38.4\%38.4% fewer. As a result, total online execution time is 56.1%56.1\%56.1% shorter than the previous work adopting the same settings. Although the computation costs of our protocols are more expensive than those of previous work, we confirm via experiments that such a disadvantage has small effects on the whole online performance in the typical WAN environments.
Secure multi-party computation (MPC) provides provable security guarantees for many privacy critical applications. The semi-honest MPC protocols are secure against semi-honest adversaries who can only observe the protocol execution, while the maliciously secure MPC protocols are secure against malicious adversaries who can deviate from the protocol description arbitrarily. Many security sensitive applications tend to use semi-honest MPC protocols because malicious security comes with huge communication and/or computation costs. In this work, we show how to efficiently transform generic semi-honest two-party protocols into maliciously secure multi-party protocol in the server-aided setting. We further propose an optimized constant-round server-aided MPC protocol. The proposed protocols are secure when all but one parties are maliciously corrupted, while the remaining party and the server are corrupted by semi-honest and non-colluding adversaries. We implement and evaluate our constant-round protocol. For the 2-party case, our protocol is only 1.11× slower than thesemi-honestYao's Garbled Circuits protocol, and it is 9.16× faster than the maliciously secure authenticated garbling protocol and 4.96× faster than the state-of-the-art maliciously secure server-aided protocol of Wuet al.For the 8-party case, our protocol is 103.29× faster than the authenticated garbling protocol and 17.03× faster than the protocol of Wuet al.
parties to securely compute an agreed function f over some finite field in the presence of a computationally unbounded adversary, who can maliciously corrupt any t out of the n parties. Most of the known efficient MPC protocols are designed in the offline- online framework introduced in a seminal work by Beaver in CRYPTO 1991. In this framework, the parties generate shared random and private multiplication-triples during the offline phase, which are used later in the online phase for securely evaluating the multiplication gates in the circuit representing f . The efficiency of the MPC protocols in this framework then relies on efficient ways of implementing the offline phase. In this paper, we propose a new and simple framework for generating shared and private random multiplication triples with unconditional security. The existing protocols approach this problem by first producing shared pairs of private and random values, followed by securely computing the shared product of each pair of values. The latter task involves a multiplication protocol for shared values that are typically communication intensive. Our framework takes a completely different approach and shuns the use of multiplication protocol. Namely, we ask the parties to verifiably share random multiplication triples and then securely extract shared random multiplication triples unknown to the adversary, from the shared triples. Realizing our framework in the asynchronous and hybrid network setting,1 we present the first ever MPC protocols with a linear (in the number of parties) communication overhead per multiplication gate in the circuit representing f . These are significant improvements over the best known existing MPC protocols in the asynchronous and hybrid network setting with communication complexity O(n2) and O(n3), respectively. Our framework when applied to the synchronous setting results in round-efficient MPC protocols.
Secure Multi-Party Computation (MPC) protocols allow a group of mutually distrusting users to compute a function jointly on their inputs without revealing any information beyond the output. For many years, implementations of MPC protocols have targeted security against semi-honest adversaries, i.e., attackers are assumed to execute the protocol honestly but try to learn private information after the fact. Protocols secure against stronger and more realistic malicious adversaries, who could behave arbitrarily during the protocol execution, were known to exist but were much less efficient. This thesis introduces a new paradigm to construct extremely efficient MPC protocols with malicious security. In particular, this thesis consists of three major contributions. 1. We introduce the authenticated garbling framework, and present an efficient concrete instantiation of the protocol. The resulting protocol partially closes the gap between semi-honest and malicious MPC protocols asymptotically; the implementation of the protocol represents the state-of-the-art system for malicious two-party computation. 2. We discuss how to apply authenticated garbling to the multi-party setting, where all-but-one parties can be corrupted by the adversary. The resulting protocol improves upon the best previous constant-round protocol by orders of magnitude. We also present a system that, for the first time, enables MPC executions among hundreds of parties, distributed globally. 3. We present a series of optimizations to two-party authenticated garbling by interpreting authenticated garbling in a new way. The improved malicious protocol has essentially the same concrete efficiency as the best semi-honest protocol in the preprocessing model. 4. We develop these protocols in EMP-toolkit, a practical and efficient MPC tool that can be used to build new protocols and to develop applications using our existing protocols.
Secure Multi-party Computation (MPC) allows a set of mutually distrusting parties to jointly evaluate a function on their private inputs while maintaining input privacy. In this work, we improve semi-honest secure two-party computation (2PC) over rings, with a focus on the efficiency of the online phase. We propose an efficient mixed-protocol framework, outperforming the state-of-the-art 2PC framework of ABY. Moreover, we extend our techniques to multi-input multiplication gates without inflating the online communication, i.e., it remains independent of the fan-in. Along the way, we construct efficient protocols for several primitives such as scalar product, matrix multiplication, comparison, maxpool, and equality testing. The online communication of our scalar product is two ring elements irrespective of the vector dimension, which is a feature achieved for the first time in the 2PC literature. The practicality of our new set of protocols is showcased with four applications: i) AES S-box, ii) Circuit-based Private Set Intersection, iii) Biometric Matching, and iv) Privacy-preserving Machine Learning (PPML). Most notably, for PPML, we implement and benchmark training and inference of Logistic Regression and Neural Networks over LAN and WAN networks. For training, we improve online runtime (both for LAN and WAN) over SecureML (Mohassel et al., IEEE S&P '17) in the range 1.5x–6.1x, while for inference, the improvements are in the range of 2.5x–754.3x.
Secure multiparty computation enables a set of parties to securely carry out a joint computation on their private inputs without revealing anything but the output. A particularly motivated setting is that of three parties with a single corruption (hereafter denoted 3PC). This 3PC setting is particularly appealing for two main reasons: (1) it admits more efficient MPC protocols than in other standard settings; (2) it allows in principle to achieve full security (and fairness). Highly efficient protocols exist within this setting with security against a semi-honest</> adversary; however, a significant gap remains between these and protocols with stronger security against a malicious</> adversary. In this paper, we narrow this gap within concretely efficient protocols. More explicitly, we have the following contributions: Concretely Efficient Malicious 3PC. We present an optimized 3PC protocol for arithmetic circuits over rings with (amortized) communication of 1 ring element per multiplication gate per party, matching the best semi-honest protocols. The protocol applies also to Boolean circuits, significantly improving over previous protocols even for small circuits. Our protocol builds on recent techniques of Boneh et al. (Crypto 2019) for sublinear zero-knowledge proofs on distributed data, together with an efficient semi-honest protocol based on replicated secret sharing (Araki et al., CCS 2016). We present a concrete analysis of communication and computation costs, including several optimizations. For example, for 40-bit statistical security, and Boolean circuit with a million (nonlinear) gates, the overhead on top of the semi-honest protocol can involve less than 0.5KB of communication for the entire circuit,</> while the computational overhead is dominated by roughly 30 multiplications per gate in the field F247. In addition, we implemented and benchmarked the protocol for varied circuit sizes. Full Security. We augment the 3PC protocol to further provide full security</> (with guaranteed output delivery) while maintaining amortized 1 ring element communication per party per multiplication gate, and with hardly any impact on concrete efficiency. This is contrasted with the best previous 3PC protocols from the literature, which allow a corrupt party to mount a denial-of-service attack without being detected.