English

Efficient Fuzzy Private Set Intersection from Secret-shared OPRF

Cryptography and Security 2026-04-17 v1

Abstract

Private set intersection (PSI) enables a sender holding a set QQ of size mm and a receiver holding a set WW of size nn to securely compute the intersection QWQ \cap W. Fuzzy PSI (FPSI) is a PSI variant where the receiver learns the items qQq \in Q for which there exists some wWw \in W satisfying dist(q,w)δ\mathsf{dist}(q, w) \le \delta under a given distance metric. Although several FPSI works are proposed for LpL_{p} distance metrics with p[1,]p \in [1, \infty], they either heavily rely on expensive homomorphic encryptions, or incur undesirable complexity, e.g., exponential to the element dimension, both of which lead to poor practical efficiency. In this work, we propose efficient FPSI protocols for Lp[1,]L_{p \in [1, \infty]} distance metrics, primarily leveraging significantly cheaper symmetric-key operations. Our protocols achieve linear communication and computation complexity in the set sizes m,nm,n, the dimension dd, and the distance threshold δ\delta. Our core building block is an oblivious programmable PRF with secret-shared outputs, which may be of independent interest. Furthermore, we incorporate a prefix technique that reduces the dependence on the distance threshold δ\delta to logarithmic, which is particularly suitable for large δ\delta. We implement our FPSI protocols and compare them with state-of-the-art constructions. Experimental results demonstrate that our protocols consistently and significantly outperform existing works across all settings. Specifically, our protocols achieve a speedup of 12145×12{\sim}145\times in running time and a reduction of 38×3{\sim}8\times in communication cost compared to Gao et al.~(ASIACRYPT'24) and a speedup of 980×9{\sim}80\times in running time and a reduction of 519×5{\sim}19\times in communication cost compared to Dang et al.~(CCS'25).

Keywords

Cite

@article{arxiv.2604.14909,
  title  = {Efficient Fuzzy Private Set Intersection from Secret-shared OPRF},
  author = {Xinpeng Yang and Meng Hao and Chenkai Weng and Robert H. Deng and Yonggang Wen and Tianwei Zhang},
  journal= {arXiv preprint arXiv:2604.14909},
  year   = {2026}
}

Comments

Accepted to the 2026 IEEE Symposium on Security and Privacy (SP)

R2 v1 2026-07-01T12:12:29.932Z