Linear Private Set Union from Multi-Query Reverse Private Membership Test
Cong Zhang, Yu Chen, Weiran Liu, Min Zhang, Dongdai Lin
摘要
Private set union (PSU) protocol enables two parties, each holding a set, to compute the union of their sets without revealing anything else to either party. So far, there are two known approaches for constructing PSU protocols. The first mainly depends on additively homomorphic encryption (AHE), which is generally inefficient since it needs to perform a non-constant number of homomorphic computations on each item. The second is mainly based on oblivious transfer and symmetric-key operations, which is recently proposed by Kolesnikov et al. (ASIACRYPT 2019). It features good practical performance, which is several orders of magnitude faster than the first one. However, neither of these two approaches is optimal in the sense that their computation and communication complexity are not both O(n), where n is the size of the set. Therefore, the problem of constructing the optimal PSU protocol remains open. In this work, we resolve this open problem by proposing a generic framework of PSU from oblivious transfer and a newly introduced protocol called multi-query reverse private membership test (mq-RPMT). We present two generic constructions of mq-RPMT. The first is based on symmetric-key encryption and general 2PC techniques. The second is based on re-randomizable public-key encryption. Both constructions lead to PSU with linear computation and communication complexity. We implement our two PSU protocols and compare them with the state-of-the-art PSU. Experiments show that our PKE-based protocol has the lowest communication of all schemes, which is 3.7 -14.8× lower depending on set size. The running time of our PSU scheme is 1.2 -12× faster than that of state-of-the-art depending on network environments.
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引用它的顶会 Paper13
- Scalable Private Set Union, with Stronger SecurityYanxue Jia, Shi-Feng Sun, Hong-Sheng Zhou, Dawu GuUSENIX Security 2024 · 被引用 22 次
- PULSE: Parallel Private Set Union for Large-Scale EntitiesJiahui Gao, Son Nguyen, Marina Blanton, Ni TrieuCCS 2025 · 被引用 1 次
- Select-Then-Compute: Encrypted Label Selection and Analytics over Distributed Datasets using FHENirajan Koirala, Seunghun Paik, Sam Martin, Helena Berens 等NDSS 2026 · 被引用 1 次
- Efficient Private Filtering and Aggregation for Weighted Set Intersection via Oblivious Encrypted Weight TransferXiaodong Wang, Shengzhe Meng, Zijie Lu, Bei LiangCCS 2026
- MinBucket MPSI: Breaking the Max-Size Bottleneck in Multi-Party Private Set IntersectionBinbin Tu, Boyudong Zhu, Yang Cao, Yu ChenNDSS 2026
它引用的顶会 Paper11
- Efficient Batched Oblivious PRF with Applications to Private Set IntersectionVladimir Kolesnikov, Ranjit Kumaresan, Mike Rosulek, Ni TrieuCCS 2016 · 被引用 429 次
- Efficient Two-Round OT Extension and Silent Non-Interactive Secure ComputationElette Boyle, Geoffroy Couteau, Niv Gilboa, Yuval Ishai 等CCS 2019 · 被引用 238 次
- PSI from PaXoS: Fast, Malicious Private Set IntersectionBenny Pinkas, Mike Rosulek, Ni Trieu, Avishay YanaiEUROCRYPT 2020 · 被引用 198 次
- VOLE-PSI: Fast OPRF and Circuit-PSI from Vector-OLEPeter Rindal, Phillipp SchoppmannEUROCRYPT 2021 · 被引用 159 次
- Private Set Intersection in the Internet Setting from Lightweight Oblivious PRFMelissa Chase, Peihan MiaoCRYPTO 2020 · 被引用 158 次
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