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Cryptography

Fair and Secure Multi-Party Computation with Cheater Detection

Minhye Seo

Published Aug 12, 2021• 15 citations
Publisher

Abstract

Secure multi-party computation (SMC) is a cryptographic protocol that allows participants to compute the desired output without revealing their inputs. A variety of results related to increasing the efficiency of SMC protocol have been reported, and thus, SMC can be used in various applications. With the SMC protocol in smart grids, it becomes possible to obtain information for load balancing and various statistics, without revealing sensitive user information. To prevent malicious users from tampering with input values, SMC requires cheater detection. Several studies have been conducted on SMC with cheater detection, but none of these has been able to guarantee the fairness of the protocol. In such cases, only a malicious user can obtain a correct output prior to detection. This can be a critical problem if the result of the computation is real-time information of considerable economic value. In this paper, we propose a fair and secure multi-party computation protocol, which detects malicious parties participating in the protocol before computing the final output and prevents them from obtaining it. The security of our protocol is proven in the universal composability framework. Furthermore, we develop an enhanced version of the protocol that is more efficient when computing an average after detecting cheaters. We apply the proposed protocols to a smart grid as an application and analyze their efficiency in terms of computational cost.

DOI
10.3390/cryptography5030019

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Secure multi-party computation (SMC) is a cryptographic protocol that allows participants to compute the desired output without revealing their inputs. A variety of results related to increasing the efficiency of SMC protocol have been reported, and thus, SMC can be used in various applications. With the SMC protocol in smart grids, it becomes possible to obtain information for load balancing and various statistics, without revealing sensitive user information. To prevent malicious users from tampering with input values, SMC requires cheater detection. Several studies have been conducted on SMC with cheater detection, but none of these has been able to guarantee the fairness of the protocol. In such cases, only a malicious user can obtain a correct output prior to detection. This can be a critical problem if the result of the computation is real-time information of considerable economic value. In this paper, we propose a fair and secure multi-party computation protocol, which detects malicious parties participating in the protocol before computing the final output and prevents them from obtaining it. The security of our protocol is proven in the universal composability framework. Furthermore, we develop an enhanced version of the protocol that is more efficient when computing an average after detecting cheaters. We apply the proposed protocols to a smart grid as an application and analyze their efficiency in terms of computational cost.
The growth of the Internet has triggered tremendous opportunities for cooperative computation, where people are jointly conducting computation tasks based on the private inputs they each supply. These computations could occur between mutually untrusted parties, or even between competitors. Today, to conduct such computations, one entity must usually know the inputs from all the participants; however if nobody can be trusted enough to know all the inputs, privacy will become a primary concern. This problem is referred to as Secure Multi-party Computation Problem (SMC) in the literature. Research in the SMC area has been focusing on only a limited set of specific SMC problems, while privacy concerned cooperative computations call for SMC studies in a variety of computation domains. About the specific SMC problems, have some result [6,7,8,9,11,12,13], and all the result are concern Two-party computations. Recently, the paper of China has [23~28].
Abstract Secure multi-party computation(SMPC) is an important research area in cryptography with many application scenarios, but there are still many problems to be solved. Aiming at security and fairness issues in SMPC, we consider that semi-honest participants are able to execute the protocol according to the specification, but there would be some additional malicious operations such as collusion and refuse to exchange information in the process of information interaction, which leads to deviations in the security and fairness of the protocol. To solve the above problems, we combine information entropy and mutual information to propose an n-round information exchange protocol, in which each participant broadcasts a relevant information value in each round without revealing additional information. The uncertainty of the correct result value is fuzzed by the interactive information in each round, and each participant cannot determine the correct result value until the end of the protocol, which effectively prevents malicious behavior and ensures the correct execution of the protocol. Security analysis and fairness analysis show that under the semi-honest model, our protocol guarantees the security and relative fairness of the output obtained by the participants after completing the protocol.
Multi-party fair exchange (MFE) and fair secure multi-party computation (fair SMPC) are under-studied fields of research, with practical importance. In particular, we consider MFE scenarios where at the end of the protocol, either every participant receives every other participant’s item, or no participant receives anything. We analyze the case where a trusted third party (TTP) is optimistically available, although we emphasize that the trust put on the TTP is only regarding the fairness , and our protocols preserve the privacy of the exchanged items against the TTP. In the fair SMPC case, we prove that a malicious TTP can only harm fairness, but not security . We construct an asymptotically optimal multi-party fair exchange protocol that requires a constant number of rounds (in comparison to linear) and O(n 2 ) messages (in comparison to cubic), where n is the number of participating parties. In our protocol, we enable the parties to efficiently exchange any item that can be efficiently put into a verifiable encryption (e.g., signatures on a contract). We show how to apply this protocol on top of any SMPC protocol to achieve fairness with very little overhead (independent of the circuit size). We then generalize our protocol to efficiently handle any exchange topology (participants exchange items with arbitrary other participants). Our protocol guarantees fairness in its strongest sense: even if all n-1 other participants are malicious and colluding with each other, the fairness is still guaranteed.
With the development of modern internet and mobile networks, there is an increasing need for privacy-preserving cooperative computation and cloud computing. Secure multi-party computation (SMPC) gives a general solution to these applications and has become a hot topic in privacy-carrying protocols. The commit-prove-fair-open protocol is one of multi-party fair exchange protocols against the malicious adversary in breaking the fair play of the participants, and it provides an important tool of SMPC to make it possible to achieve the fairness with corrupted majority according to the standard real/ideal world simulation paradigm framework. In this paper, we at first prove two lemmas about the simplified Camenisch-Shoup commitment and the time-lines, and then propose a very efficient resource-fair commit-prove-fair-open protocol. Compared with the other commit-prove-fair-open protocols, our new protocol enjoys two important advantages: 1) communications cost and computations price are less than 20%; 2) it allows commitment to obtain value 0, which is not implemented in the other constructions.
Secure multi-party computation(SMPC) is an important research field in cryptography, secure multi-party computation has a wide range of applications in practice. Accordingly, information security issues have arisen. Aiming at security issues in Secure multi-party computation, we consider that semi-honest participants have malicious operations such as collusion in the process of information interaction, gaining an information advantage over honest parties through collusion which leads to deviations in the security of the protocol. To solve this problem, we combine information entropy to propose an n-round information exchange protocol, in which each participant broadcasts a relevant information value in each round without revealing additional information. Through the change of the uncertainty of the correct result value in each round of interactive information, each participant cannot determine the correct result value before the end of the protocol. Security analysis shows that our protocol guarantees the security of the output obtained by the participants after the completion of the protocol.
Effective multi-party computation protocols have been developed, but concerns regarding privacy and correctness persist. Classic results demonstrate that guaranteed output delivery can be achieved by assuming fairness and identifiable abort. However, if the majority is malicious, it is still challenging to design an efficient implementation that can deliver correct outputs while maintaining robustness and fairness. To address this issue, we have redesigned the secret-sharing mechanism and employed a semi-trusted third party (TTP) as the key manager to provide optimistic backup for output delivery. The verification and delivery procedures prevent the malicious parties from “stealing” the output, when there is at least one honest party. Furthermore, the TTP has no knowledge of output, so even if he is malicious and colluding, we only lose fairness. The decryption is needed only when misconduct is detected. Our scheme also enables identified abort for offline preprocessing, and the audit of the offline sub-protocols can be publicly performed, holding corrupted parties accountable before receiving private inputs. With fairness and identifiable abort, output delivery is guaranteed by excluding the cheaters.