Private, secure and truthful multi-party protocols

Carmit Hazay, Yehuda Lindell

Xue Ge, Jiawei Dou, Wenli Wang +1 more

Abstract Applying secure multi‐party computation (SMC) to implement secure linear programming is an important problem of SMC. Private feasible solution determination means that one of the participants has a private value and the other participants have some constraints, and they want to cooperatively determine whether the private value satisfies the constraints without disclosing their private information. This problem has important theoretical and practical significance in both scientific research and practice. In this study, the authors propose a protocol based on elliptic curve cryptosystem for this problem and prove that the protocol is secure in the semi‐honest model. Furthermore, threshold decryption elliptic curve cryptosystem is used to privately determine a feasible solution with multiple constraints for two‐party and multi‐party scenarios. The efficiency analysis shows that the protocols developed in this study are simple and efficient. Finally, the authors also show how to use these protocols to solve other SMC problems.

Takashi Satoh, Kaoru Kurosawa, Shigeo Tsujii

Zixian Li, Wenjie Liu, Bing-Mei Su

Private set intersection (PSI) has important application value, however, current quantum PSI protocols are either unsuitable for multi-party scenarios or inefficient. Recently, Imran (arXiv: 2303.17196v3 , 2023) proposed two quantum secure multi-party greatest common divisor (GCD) protocols that can be used for PSI, but with the downside of information leakage and resource consumption. In this paper, we propose a novel quantum secure multi-party GCD protocol that has higher security and lower complexity. To hide privacy, each party randomly selects a coefficient within a range determined by his input integer, and with the assistance of a semi-honest third party TP, all parties secretly calculate the linear combination of their inputs under these coefficients. Once enough linear combinations are collected, TP calculates the GCD of these combinations, which is equal to the GCD of all input integers. To verify the honesty of participants, a quantum zero-knowledge proof sub-protocol is designed. Analysis shows that our GCD protocol is correct and has security against malicious attacks. Moreover, its complexity is polynomial level and lower than Imran’s. Furthermore, we demonstrate the scalability of our GCD protocol in private set operations, such as private set intersection, private set intersection cardinality, private multi-set intersection, etc.

Andreas Klinger, Felix Battermann, Ulrike Meyer

In secure multi-party computation (SMPC), it is considered that multiple parties that are known to each other evaluate a function over their private inputs in a secure fashion. The participating parties do not learn anything about each other's private inputs beyond what can be deduced from their own input and output. The assumption that the parties know each other, however, does not seem suitable for all potential applications of SMPC. In some applications participants may not only want to hide their private inputs and outputs, but may also want to hide the fact that they are participating in a given function evaluation in the first place. We therefore propose an anonymous system for SMPC that allows parties to anonymously evaluate a function of their private inputs in a fully distributed and secure fashion. The proposed system allows authorized parties to execute an SMPC protocol robust with penalty against a dishonest majority in the presence of a malicious adversary. During the protocol execution, the system guarantees that all participating parties stay anonymous w. r. t. each other as well as any third parties. In addition, it guarantees that in each function evaluation all participating parties are unique, i. e., no party can participate as more than one entity.

Yehuda Lindell