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Lecture notes in computer science

Optimally-Fair Multi-party Exchange Without Trusted Parties

Ivo Maffei, Andrew William Roscoe

Published Jan 1, 2024• 1 citation
Publisher

Abstract

Abstract We present a multi-party exchange protocol that achieves optimal partial fairness even in the presence of a dishonest majority. We demonstrate how this protocol can be applied to any type of multi-party exchange scenario where the network topology is complete. When combined with standard secure multi-party computation techniques, our protocol enables SMPC with partial fairness when a dishonest majority is involved. Fairness optimality is proven in an abstract model which applies to all protocols based on the concept of concealing the point when the secrets are exchanged. Our protocol improves known results via the use of timed-release encryption and commutative blinding.

DOI
10.1007/978-3-031-50594-2_16

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Abstract We present a multi-party exchange protocol that achieves optimal partial fairness even in the presence of a dishonest majority. We demonstrate how this protocol can be applied to any type of multi-party exchange scenario where the network topology is complete. When combined with standard secure multi-party computation techniques, our protocol enables SMPC with partial fairness when a dishonest majority is involved. Fairness optimality is proven in an abstract model which applies to all protocols based on the concept of concealing the point when the secrets are exchanged. Our protocol improves known results via the use of timed-release encryption and commutative blinding.
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.
Abstract We propose a new fair exchange protocol that takes advantage of delay encryption and commutative encryption to achieve optimal partial fairness among all protocols involving one-way messages. Our protocol consists of 3 setup messages and 2N+12N+12N+1 2 N + 1 exchange messages and it is fair against covert adversaries with probability 1−12N1- \frac{1}{2N}1−2N1​ 1 - 1 2 N . We prove that this is optimal up to shortening the setup phase which is notably more efficient than existing protocols.
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.
Secure multiparty computation allows mutually distrusting parties to compute a function on their private inputs such that nothing but the function output is revealed. Achieving fairness --- that all parties learn the output or no one does -- is a long studied problem with known impossibility results in the standard model if a majority of parties are dishonest. We present a new model for achieving fairness in MPC against dishonest majority by using public bulletin boards implemented via existing infrastructure such as blockchains or Google's certificate transparency logs. We present both theoretical and practical constructions using either witness encryption or trusted hardware (such as Intel SGX). Unlike previous works that either penalize an aborting party or achieve weaker notions such as Δ\DeltaΔ-fairness, we achieve complete fairness using existing infrastructure.
Abstract We study the problem of constructing secure multi-party computation (MPC) protocols thatare completely fair-- meaning that either all the parties learn the output of the function, or nobody does-- even when a majority of the parties are corrupted. We first propose a framework for fairmulti-party computation, within which we formulate a definition of secure and fair protocols. The definition follows the standard simulation paradigm, but is modified to allow the protocol to dependon the runing time of the adversary. In this way, we avoid a well-known impossibility result for fair MPC with corrupted majority; in particular, our definition admits constructions that tolerate upto ( n- 1) corruptions, where n is the total number of parties. Next, we define a "commit-prove-fair-open " functionality and construct an efficient protocol that realizes it, using a new variant of a cryptographic primitive known as "time-lines. " With this functionality, we show that some ofthe existing secure MPC protocols can be easily transformed into fair protocols while preserving their security. Putting these results together, we construct efficient, secure MPC protocols that arecompletely fair even in the presence of corrupted majorities. Furthermore, these protocols remain secure when arbitrarily composed with any protocols, which means, in particular, that they areconcurrently-composable and non-malleable. Finally, as an example of our results, we show a very efficient protocol that fairly and securely solves the socialist millionaires ' problem.
Recently developed cryptographic techniques make it possible to construct fair exchange protocols with an off-line trusted third party (TTP). The technique is referred to as a verifiable encryption scheme (VES) and proves that a ciphertext is the result of the encryption of a specified value without revealing this value. In this paper we apply the technique to multi-party fair exchange (MPFE) protocols which leads to the trusted neutral party (TNP, it is not the third party in multi-party protocols) involved in the protocol to be off-line. Multi-party fair exchange has been studied by Asokan et al. (1996) and Franklin and Tsudik (1998) where the TNP is on-line. For off-line TNP-based MPFE, the issues are different from that of on-line TNP MPFE. We give a definition of fairness of the MPFE with off-line TNP. We then present our MPFE protocol and prove its fairness.