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Paper 2021/882

Computational Hardness of Optimal FairComputation: Beyond Minicrypt

Hemanta K. Maji and Mingyuan Wang

Abstract

Secure multi-party computation allows mutually distrusting parties to compute securely over their private data. However, guaranteeing output delivery to honest parties when the adversarial parties may abort the protocol has been a challenging objective. As a representative task, this work considers two-party coin-tossing protocols with guaranteed output delivery, a.k.a., fair coin-tossing. In the information-theoretic plain model, as in two-party zero-sum games, one of the parties can force an output with certainty. In the commitment-hybrid, any $r$-message coin-tossing protocol is ${1/\sqrt r}$-unfair, i.e., the adversary can change the honest party's output distribution by $1/\sqrt r$ in the statistical distance. Moran, Naor, and Segev (TCC--2009) constructed the first $1/r$-unfair protocol in the oblivious transfer-hybrid. No further security improvement is possible because Cleve (STOC--1986) proved that $1/r$-unfairness is unavoidable. Therefore, Moran, Naor, and Segev's coin-tossing protocol is optimal. However, is oblivious transfer necessary for optimal fair coin-tossing? Maji and Wang (CRYPTO--2020) proved that any coin-tossing protocol using one-way functions in a black-box manner is at least $1/\sqrt r$-unfair. That is, optimal fair coin-tossing is impossible in Minicrypt. Our work focuses on tightly characterizing the hardness of computation assumption necessary and sufficient for optimal fair coin-tossing within Cryptomania, outside Minicrypt. Haitner, Makriyannia, Nissim, Omri, Shaltiel, and Silbak (FOCS--2018 and TCC--2018) proved that better than $1/\sqrt r$-unfairness, for any constant $r$, implies the existence of a key-agreement protocol. We prove that any coin-tossing protocol using public-key encryption (or, multi-round key agreement protocols) in a black-box manner must be $1/\sqrt r$-unfair. Next, our work entirely characterizes the additional power of secure function evaluation functionalities for optimal fair coin-tossing. We augment the model with an idealized secure function evaluation of $f$, \aka, the $f$-hybrid. If $f$ is complete, that is, oblivious transfer is possible in the $f$-hybrid, then optimal fair coin-tossing is also possible in the $f$-hybrid. On the other hand, if $f$ is not complete, then a coin-tossing protocol using public-key encryption in a black-box manner in the $f$-hybrid is at least $1/\sqrt r$-unfair.

Metadata
Available format(s)
PDF
Category
Foundations
Publication info
A minor revision of an IACR publication in CRYPTO 2021
Keywords
Fair computationOptimal fair coin-tossingCryptomaniaBlack-box separationHardness of computation resultsSecure function evaluation functionalities
Contact author(s)
wang1929 @ purdue edu
History
2021-06-29: received
Short URL
https://ia.cr/2021/882
License
Creative Commons Attribution
CC BY

BibTeX

@misc{cryptoeprint:2021/882,
      author = {Hemanta K.  Maji and Mingyuan Wang},
      title = {Computational Hardness of Optimal {FairComputation}: Beyond Minicrypt},
      howpublished = {Cryptology {ePrint} Archive, Paper 2021/882},
      year = {2021},
      url = {https://eprint.iacr.org/2021/882}
}
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