Distance-Aware Private Set Intersection

Authors: 

Anrin Chakraborti, Duke University; Giulia Fanti, Carnegie Mellon University; Michael K. Reiter, Duke University

Abstract: 

Private set intersection (PSI) allows two mutually untrusting parties to compute an intersection of their sets, without revealing information about items that are not in the intersection. This work introduces a PSI variant called distance-aware PSI (DA-PSI) for sets whose elements lie in a metric space. DAPSI returns pairs of items that are within a specified distance threshold of each other. This paper puts forward DA-PSI constructions for two metric spaces: (i) Minkowski distance of order 1 over the set of integers (i.e., for integers a and b, their distance is |a−b|); and (ii) Hamming distance over the set of binary strings of length ℓ. In the Minkowski DA-PSI protocol, the communication complexity scales logarithmically in the distance threshold and linearly in the set size. In the Hamming DA-PSI protocol, the communication volume scales quadratically in the distance threshold and is independent of the dimensionality of string length ℓ. Experimental results with real applications confirm that DA-PSI provides more effective matching at lower cost than naïve solutions.

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BibTeX
@inproceedings {285467,
author = {Anrin Chakraborti and Giulia Fanti and Michael K. Reiter},
title = {{Distance-Aware} Private Set Intersection},
booktitle = {32nd USENIX Security Symposium (USENIX Security 23)},
year = {2023},
isbn = {978-1-939133-37-3},
address = {Anaheim, CA},
pages = {319--336},
url = {https://www.usenix.org/conference/usenixsecurity23/presentation/chakraborti-intersection},
publisher = {USENIX Association},
month = aug
}

Presentation Video