Labeled Private Set Intersection From Distributed Point Function

Qi Liu, Xiaojie Guo*, Kang Yang, Yu Yu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Private Set Intersection (PSI) allows two mutually distrusting parties to compute the intersection of their sets without revealing any additional information, and has found numerous applications. A part of applications require labeled PSI in the unbalanced setting, where a server holds a label for each item in a set that is much larger than the set held by a client, and the client obtains the intersection and the corresponding labels. In this paper, we present a new concretely efficient labeled PSI protocol in the unbalanced setting, without using computation-heavy homomorphic encryption. Our protocol is based on Distributed Point Function (DPF) with hardware acceleration from fixed-key AES-NI, and has communication complexity linear in the size of a small set of the client and sublinear in the size of a large set of the server. Our protocol exploits two Oblivious Pesudorandom Function (OPRF) protocols, based on Diffle-Hellman PRFs or block ciphers, to achieve a trade-off between computation and communication. Our implementation demonstrates that our protocol outperforms the previous labeled and unbalanced PSI protocols. In particular, for two sets with respective 2^{24} and 1 items, where each item has a 32-byte label, our protocol takes 1.19 seconds for an end-to-end performance, resulting in 26 × improvement compared to the state-of-the-art protocol by Cong et al. (CCS 2021). In terms of the cost of the one-time initialization, we speed up the computations more than 325× in the above comparison.

Original languageEnglish
Pages (from-to)2970-2983
Number of pages14
JournalIEEE Transactions on Information Forensics and Security
Volume20
DOIs
StatePublished - 2025
Externally publishedYes

Keywords

  • Labeled private set intersection
  • distributed point function
  • oblivious pseudorandom function

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