Efficient Multi-Party Private Set Intersection with Better Security

We introduce Zero-share-Xor Garbled Bloom Filter and an efficient PSI protocol using oblivious pseudorandom function (OPRF). Our approach enhances security based on Chase et al. (Crypto'20). By minimizing heavy cryptographic primitives and relying mainly on symmetric-key encryption with necessary base OTs, our protocols achieve superior performance. It is secure against semi-honest adversaries and support collusion among clients (with at least two honest clients). Our experiments evaluation, utilizing multithreading to simulate protocol steps, demonstrates optimal concurrency under star-like and path-like communication graphs. Comparisons with state-of-the-art symmetric protocols show our MPSI protocols outperforming others in scalability and performance across varying numbers of parties and set sizes.

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Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/eiecs63941.2024.10800597
Primary Topic
Cryptography and Data Security
Type
article
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article

Efficient Multi-Party Private Set Intersection with Better Security

Zhenfu Cao, Jiachen Shen, K. Xu, Xiaolei Dong
Cryptography and Data Security
article

Efficient Multi-Party Private Set Intersection with Better Security

Zhenfu Cao, Jiachen Shen, K. Xu, Xiaolei Dong
article en

Abstract

We introduce Zero-share-Xor Garbled Bloom Filter and an efficient PSI protocol using oblivious pseudorandom function (OPRF). Our approach enhances security based on Chase et al. (Crypto'20). By minimizing heavy cryptographic primitives and relying mainly on symmetric-key encryption with necessary base OTs, our protocols achieve superior performance. It is secure against semi-honest adversaries and support collusion among clients (with at least two honest clients). Our experiments evaluation, utilizing multithreading to simulate protocol steps, demonstrates optimal concurrency under star-like and path-like communication graphs. Comparisons with state-of-the-art symmetric protocols show our MPSI protocols outperforming others in scalability and performance across varying numbers of parties and set sizes.

Shanghai Key Laboratory of Trustworthy Computing (CN), East China Normal University (CN)
Sustainable cities and communities
Openalex Percentile: Top 78%
Cryptography and Data Security
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