Faster Private Set Intersection Based on OT Extension

By Benny Pinkas, Thomas Schneider, Michael Zohner. USENIX Security Symposium, 2014

419 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/2bcbd6aa35d6f360dae49bfce5019c9e7a3a73c6

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Citations in the corpus

MASCOT: Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (2016, unknown): “Pinkas et al. [37, 38] used OT extensions to achieve a very eﬃcient and scalable protocol for the dedicated application of private set intersection.”
Scalable Private Set Intersection Based on OT Extension (2018, methodology): “In this section, we describe our new OT-based PSI protocol, of which an earlier version appeared in [Pinkas et al. 2014; Pinkas et al. 2015].”
Efficient Batched Oblivious PRF with Applications to Private Set Intersection (2016, methodology): “In [17], SOT for k-bit selection strings is built by executing k 1-out of-2 OTs, and this technique is also essentially what is used in the PSI protocol of [27].”
An Efficient Toolkit for Computing Private Set Operations (2017, background): “The existing works of [23,22,19] provide even faster designs though these use inherently symmetric primitives which are not comparable with our work.”
Fast Private Set Intersection from Homomorphic Encryption (2017, background): “[49], and later improved in [37, 46, 50].”
Phasing: Private Set Intersection Using Permutation-based Hashing (2015, methodology): “The only PSI protocol described in the recent survey in [PSZ14] that is not based on the random oracle model is the protocol of [FNP04] which uses oblivious polynomial evaluation based on El-Gamal encryption, but that protocol is considerably less efﬁcient than other state-of-the-art PSI protocols.”
Improved Private Set Intersection Against Malicious Adversaries (2017, methodology): “[23] suggested an optimization that eliminates the need for Alice to send her entire masked GBF.”
Asymmetrical Vertical Federated Learning (2020, background): “, 2004; Liang and Chawathe, 2004], oblivious transfer [Pinkas et al., 2014], garbled circuits [Huang et al.”
On Deploying Secure Computing Commercially: Private Intersection-Sum Protocols and their Business Applications (2019, methodology): “In this section, we describe a protocol for intersection-sum based on Random Oblivious Transfer, which is used in existing PSI solutions [45, 43, 19, 47].”
Practical Multi-party Private Set Intersection from Symmetric-Key Techniques (2017, methodology): “Finally, the condition of a collision among randomly chosen { z i } values is independent of any single z i . candidate v being chosen (and thus the overall distribution of v ) is the same regardless of whether the receiver queried F on one of It is important to discuss the parameter choice m (lengt”
Labeled PSI from Fully Homomorphic Encryption with Malicious Security (2018, methodology): “In particular, we follow the PSZ paradigm [36, 43, 45, 46], where the OPRF is applied to the items after cuckoo hashing.”
Scalable Private Set Union from Symmetric-Key Techniques (2019, methodology): “RPMT is related to the traditional Private Mem-bership Test (PMT) [46], which is a two-party protocol in which the party with input y learns whether or not its item is in the input set X of other party (who learns nothing).”
Vertical Federated Learning: Concepts, Advances, and Challenges (2022, background): “PSI protocols can be realized using various techniques, such as encryption and signature strategies [87] and oblivious transfer [88] etc.”
ABY - A Framework for Efficient Mixed-Protocol Secure Two-Party Computation (2015, methodology): “The Y-only and B-only instantiations correspond exactly to the instantiations of [64].”