Paper 2020/153 Original: eprint.iacr.org/2020/153 ↗

Constructing Secure Multi-Party Computation with Identifiable Abort

Nicholas Brandt
Sven Maier
Tobias Müller
Jörn Müller-Quade
Abstract

Composable protocols for Multi-Party Computation that provide security with Identifiable Abort against a dishonest majority require some form of setup, e.g. correlated randomness among the parties. While this is a very useful model, it has the downside that the setup's randomness must be programmable, otherwise security becomes provably impossible. Since programmability is more realistic for smaller setups (in terms of number of parties), it is crucial to minimize the correlation complexity (degree of correlation) of the setup's randomness. We give a tight tradeoff between the correlation complexity \(\beta\) and the corruption threshold \(t\). Our bounds are strong in that \(\beta\)-wise correlation is sufficient for statistical security while \(\beta-1\)-wise correlation is insufficient even for computational security. In particular, for strong security, i.e., \(t < n\), full \(n\)-wise correlation is necessary. However, for any constant fraction of honest parties, we provide a protocol with constant correlation complexity which tightens the gap between the theoretical model and the setup's implementation in the real world. In contrast, previous state-of-the-art protocols require full \(n\)-wise correlation regardless of \(t\).

Metadata
Available format(s)
PDF
Category
Cryptographic protocols
Publication info
Preprint.
History
2023-12-04: last updated
2020-02-13: published
Short URL
https://ia.cr/2020/153
License
https://creativecommons.org/licenses/by/4.0/

BibTeX

@misc{cryptoeprint:2020/153,
      author = {Nicholas Brandt and Sven Maier and Tobias Müller and Jörn Müller-Quade},
      title = {Constructing Secure Multi-Party Computation with Identifiable Abort},
      howpublished = {Cryptology {ePrint} Archive, Paper 2020/153},
      year = {2020},
      url = {https://eprint.iacr.org/2020/153}
}
Note: In order to protect the privacy of readers, this archive does not use cookies or embedded third party content.