Secure Two-Party Computation is Practical

By Benny Pinkas, Thomas Schneider, Nigel P. Smart, Stephen C. Williams. 2009

762 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

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Citations in the corpus

Prio: Private, Robust, and Scalable Computation of Aggregate Statistics (2017, background): “That said, there have been great advances in practical general-purpose MPC protocols of late [12,13,23,45,46,73,89,91,93,98].”
Privacy-Preserving Ridge Regression on Hundreds of Millions of Records (2013, methodology): “Second, using the garbled-row reduction technique [25], FastGC reduces the communication cost for k-fan-in non- XOR gates by 1/2 k , which gives a 25% communication saving , since only 2-fan-in gates are defined in the framework.”
Distributed Learning without Distress: Privacy-Preserving Empirical Risk Minimization (2018, background): “Lindell and Pinkas [31] proposed one of the earliest approaches to use MPC for private data mining, which was followed by several works considering different adversarial models or applications [55, 50, 33, 42].”
Privacy-preserving matrix factorization (2013, background): “There are presently many frameworks that implement Yao garbled circuits [45, 23, 24, 44, 53, 25, 36].”
From Keys to Databases - Real-World Applications of Secure Multi-Party Computation (2018, background): “A major research effort over the last ten years, spawned from an initial paper co-authored by Unbound Tech’s founder Smart [38], has shown that a similar situation can also be applied to evaluating symmetric cryptographic primitives such as the AES and DES block ciphers.”
Secure Two-Party Computation via Cut-and-Choose Oblivious Transfer (2011, methodology): “We remark that the protocol of [28] has been implemented for the non-trivial problem of securely computing the AES block cipher (pseudorandom function), where one party’s input is a secret key and the other party’s input is a value to be “encrypted” [38].”
Scalable Private Set Intersection Based on OT Extension (2018, methodology): “There exist several instantiations for OPRFs, described in [Freedman et al. 2005]: based on generic secure computation techniques (using an AES circuit [Pinkas et al. 2009]), based on the Difﬁe-Hellman assumption, or based on OT.”
A New Approach to Practical Active-Secure Two-Party Computation (2012, methodology): “We note, however, that using, e.g., the implementation in [PSSW09], the seed OTs could be done in around 20 seconds, so they would not signiﬁcantly aﬀect the amortized times reported.”
More efficient oblivious transfer and extensions for faster secure computation (2013, neutral): “Our optimization is also compatible with the garbled row reduction technique of [47].”
Foundations of garbled circuits (2012, background): “Other one-call, fixed-key schemes are possible, for obliviousness, authenticity, and dynamic security, and adjustments to allow the free-xor and row-reduction optimizations [31, 44].”