A Proof of Security of Yao’s Protocol for Two-Party Computation

By Yehuda Lindell, Benny Pinkas. 2009

688 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Privacy & Security

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Citations in the corpus

QUOTIENT: Two-Party Secure Neural Network Training and Prediction (2019, background): “We will not introduce the protocol in detail here, and instead, refer the reader to [37] for a detailed presentation and security analysis.”
Privacy-Preserving Distributed Linear Regression on High-Dimensional Data (2017, methodology): “For our solving phase, we use Yao’s two-party garbled circuits protocol, which was formally-described and proven secure by Lindell and Pinkas [49].”
Prio: Private, Robust, and Scalable Computation of Aggregate Statistics (2017, background): “In theory, secure multi-party computation (MPC) protocols [11, 15, 68, 90, 123] allow a set of servers, with some”
Privacy-Preserving Ridge Regression on Hundreds of Millions of Records (2013, background): “garbled circuits) [3] (see also [12]) allows the two-party evaluation of a function f(x1, x2) in the presence of semi-honest adversaries.”
SecureML: A System for Scalable Privacy-Preserving Machine Learning (2017, background): “See [32] for a more detailed description and proof of security against a semi-honest adversary.”
Private Set Intersection: Are Garbled Circuits Better than Custom Protocols? (2012, methodology): “) Thus, we need only describe the different types of circuits we construct and can rely on established proofs of security properties for garbled-circuit protocols in the semi-honest model [29].”
Quid-Pro-Quo-tocols: Strengthening Semi-honest Protocols with Dual Execution (2012, background): “3) S chooses random output-wire labels Then, in the usual way (e.g., [26]), S gives to A a simulated garbled circuit constructed in such a way that the output-wire labels learned by A (given the input-wire labels chosen by S in the ﬁrst step) will be precisely W v B A .”
Two Halves Make a Whole - Reducing Data Transfer in Garbled Circuits Using Half Gates (2015, background): “We assume some familiarity with garbled circuit constructions (for a comprehensive treatment of Yao’s classical construction see Lindell and Pinkas [23]).”