Secure Join Operations in Multi-Identifier Databases: Performance and Practicality
Summary: Introduces a semi-honest-secure multi-key inner join combining per-column Circuit PSI with private permutation, achieving 2–4× speedups while hiding matches. Ordered-left-join deduplication and optimized equality testing improve utility and throughput to 18K 4-key records/core/s. (summarized by gpt-5.6-luna on Aug 17 2026)
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Authors
- 1. Wen-jie Lu (TikTok)
- 2. Yongchuan Niu (TikTok)
- 3. Yongjun Zhao (TikTok)
- 4. Wei Dai (TikTok)
- 5. Donghang Lu (TikTok)
- 6. Li Wang (TikTok)
- 7. Qiang Yan (TikTok)
BibTeX Citation
@article{lu_vldb26,
title = {{Secure Join Operations in Multi-Identifier Databases: Performance and Practicality}},
author = {Lu, Wen-jie and Niu, Yongchuan and Zhao, Yongjun and Dai, Wei and Lu, Donghang and Wang, Li and Yan, Qiang},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {9},
pages = {1854--1866},
doi = {10.14778/3819518.3819519},
url = {https://doi.org/10.14778/3819518.3819519},
year = {2026}
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Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 68 | Privacy-Preserving Data Mining | 2000 | SIGMOD | 0.00037958605 |
| 6,128 | Cryptographically Secure Private Record Linkage Using Locality-Sensitive Hashing | 2024 | VLDB | 5.8783975e-05 |
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