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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Cryptolog...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Cryptology
Article . 2018 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2016 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
Research Collection
Conference object . 2016
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Probabilistic Termination and Composability of Cryptographic Protocols

Authors: Cohen, Ran; Coretti, Sandro; Garay, Jüan A.; Zikas, Vassilis;

Probabilistic Termination and Composability of Cryptographic Protocols

Abstract

When analyzing the round complexity of multi-party computation MPC, one often overlooks the fact that underlying resources, such as a broadcast channel, can by themselves be expensive to implement. For example, it is impossible to implement a broadcast channel by a deterministic protocol in a sub-linear in the number of corrupted parties number of rounds. The seminal works of Rabin and Ben-Or from the early 80's demonstrated that limitations as the above can be overcome by allowing parties to terminate in different rounds, igniting the study of protocols with probabilistic termination. However, absent a rigorous simulation-based definition, the suggested protocols are proven secure in a property-based manner, guaranteeing limited composability. In this work, we define MPC with probabilistic termination in the UC framework. We further prove a special universal composition theorem for probabilistic-termination protocols, which allows to compile a protocol using deterministic-termination hybrids into a protocol that uses expected-constant-round protocols for emulating these hybrids, preserving the expected round complexity of the calling protocol. We showcase our definitions and compiler by providing the first composable protocols with simulation-based security proofs for the following primitives, relying on point-to-point channels: 1 expected-constant-round perfect Byzantine agreement, 2 expected-constant-round perfect parallel broadcast, and 3 perfectly secure MPC with round complexity independent of the number of parties.

Related Organizations
Keywords

Probabilistic termination; Universal composition; Cryptographic protocols; Randomized Byzantine agreement

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Top 10%
Average
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