Near-Linear Unconditionally-Secure Multiparty Computation with a Dishonest Minority

By Eli Ben-Sasson, Serge Fehr, Rafail M. Ostrovsky. 2012

120 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Dan Boneh
2. Nigel P. Smart
3. Henry Corrigan-Gibbs
4. Ivan Bjerre Damgård
5. Marcel Keller
6. Yehuda Lindell
7. Valerio Pastro
8. Craig Gentry

In Computational Theory and Mathematics

1. Nigel P. Smart
2. Henry Corrigan-Gibbs
3. Dan Boneh
4. Ivan Bjerre Damgård
5. Marcel Keller
6. Yehuda Lindell
7. Valerio Pastro
8. Sarah Zakarias

In Information Systems

1. Nigel P. Smart
2. Henry Corrigan-Gibbs
3. Ivan Bjerre Damgård
4. Dan Boneh
5. Valerio Pastro
6. Marcel Keller
7. Sarah Zakarias
8. Yehuda Lindell

Citations in the corpus

• Prio: Private, Robust, and Scalable Computation of Aggregate Statistics (2017, methodology): “[19] use polynomial identities to check the consistency of secret-shared values in a very different MPC protocol.”
• Multiparty Computation from Somewhat Homomorphic Encryption (2012, methodology): “Our approach resembles a technique introduced by Ben-Sasson et al in [4] and one by Cramer et al in [10].”