Minimal Message Complexity of Asynchronous Multi-party Contract Signing

Mauw, Sjouke; Radomirović, Saša; Dashti, Mohammad Torabi

doi:10.1109/csf.2009.15

Cited by 21 publications

(62 citation statements)

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“…Neither allows arbitrarily interleaved messages as our Theorem 1; instead, they assume that communication steps are either totally ordered or ordered following a directed acyclic graph (DAG). In addition, both results [13,15] propose a range of the optimal efficiency for fair exchange, instead of a concrete lower-bound for fair computation in general (as does our Theorem 1).…”

Section: The Shortest Permutation Sequencementioning

confidence: 99%

“…Mauw, Radomirović and Dashti (MRD) [13] proved that the optimal number of messages of totallyordered fair contract signing schemes 13 falls between + n − 1 and + 2n − 3. Later, Mauw and Radomirović (MR) [15] generalized the result of MRD to DAG-ordered fair contract signing schemes 14 .…”

Section: The Shortest Permutation Sequencementioning

confidence: 99%

“…Later, Mauw and Radomirović (MR) [15] generalized the result of MRD to DAG-ordered fair contract signing schemes 14 . Both [13] and [15] considered fair contract signing as fair exchange of digital signatures. They use a model different from PSW, and fall within the coverage of our Theorem 1.…”

Section: The Shortest Permutation Sequencementioning

confidence: 99%

“…An idealized protocol is informally defined as a totally-ordered fair exchange protocol of which the number of messages in an optimistic execution is optimal [13]. (Here a protocol is equivalent as a Compute protocol in our Definition 1.…”

Section: The Shortest Permutation Sequencementioning

confidence: 99%

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Optimal Fair Computation

Guerraoui

Wang

2016

Lecture Notes in Computer Science

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A computation scheme among n parties is fair if no party obtains the computation result unless all other n − 1 parties obtain the same result. A fair computation scheme is optimistic if n honest parties can obtain the computation result without resorting to a trusted third party.We prove, for the first time, a tight lower bound on the message complexity of optimistic fair computation for n parties among which n − 1 can be malicious in an asynchronous network. We do so by relating the optimal message complexity of optimistic fair computation to the length of the shortest permutation sequence in combinatorics.

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Section: The Shortest Permutation Sequencementioning

confidence: 99%

Section: The Shortest Permutation Sequencementioning

confidence: 99%

Section: The Shortest Permutation Sequencementioning

confidence: 99%

Section: The Shortest Permutation Sequencementioning

confidence: 99%

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Optimal Fair Computation

Guerraoui

Wang

2016

Lecture Notes in Computer Science

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“…Mukhamedov and Ryan [44] decreased the round complexity to O(n). Lastly, Mauw et al [42] gave the lower bound of O(n 2 ) for the number of messages to achieve fairness. Their protocol requires O(n 2 ) messages, but the round complexity is not constant.…”

Section: Related Workmentioning

confidence: 99%

Optimally Efficient Multi-Party Fair Exchange and Fair Secure Multi-Party Computation

Kılınç

Küpçü

2015

Lecture Notes in Computer Science

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Multi-party fair exchange (MFE) and fair secure multi-party computation (fair SMPC) are under-studied fields of research, with practical importance. We examine MFE scenarios where every participant has some item, and at the end of the protocol, either every participant receives every other participant's item, or no participant receives anything. This is a particularly hard scenario, even though it is directly applicable to protocols such as fair SMPC or multi-party contract signing. We further generalize our protocol to work for any exchange topology. 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 even against a malicious TTP.We construct an asymptotically optimal (for the complete topology) 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. We enable the parties to efficiently exchange any item that can be efficiently put into a verifiable escrow (e.g., signatures on a contract). We show how to apply this protocol on top of any SMPC protocol to achieve a fairness guarantee with very little overhead, especially if the SMPC protocol works with arithmetic circuits. Our protocol guarantees fairness in its strongest sense: even if all n − 1 other participants are malicious and colluding, fairness will hold.

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Blockchain‐based fair three‐party contract signing protocol for fog computing

Huang

Chen

2018

Concurrency and Computation

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SummaryFog computing is a new computing paradigm that can provide flexible resources and services at the edge of network. It is an extension of cloud computing and usually cooperated with cloud computing. Therefore, end users, fog nodes, and cloud servers can form a three‐layer service model in practical application. In this model, they should have an agreement on a service contract, which contains every party's rights and obligations before the beginning of the service. However, due to lack of trust, it will suffer from some fairness problems during signing a service contract. Contract signing protocol allows two or more mutual distrust entities to sign a predefined digital contract in a fair and effective way. In this paper, we propose a fair three‐party contract signing protocol based on the primitive of blockchain, which can be applied to the scenario of fog computing. Our proposed construction allows the participants to sign a contract in a fair way without the involvement of an arbitrator. Moreover, the privacy of the contract content can be preserved on the public chain. Finally, we realize the proposed protocol through the private blockchain and provide the experimental simulation that analyzes the efficiency and effectiveness.

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Minimal Message Complexity of Asynchronous Multi-party Contract Signing

Cited by 21 publications

References 20 publications

Optimal Fair Computation

Optimal Fair Computation

Optimally Efficient Multi-Party Fair Exchange and Fair Secure Multi-Party Computation

Blockchain‐based fair three‐party contract signing protocol for fog computing

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