Bifrost: A Much Simpler Secure Two-Party Data Join Protocol for Secure Data Analytics
Summary: Bifrost delivers redundancy-free secret-shared joins using only ECDH-PSI and two-party oblivious shuffles, eliminating iPrivJoin’s OPPRF and reducing shuffle rounds via dual mapping. At 100 GB, it achieves 2.54–22.32× speedup and 84–89% lower communication, improving downstream SDA. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Shuyu Chen (Fudan University)
- 2. Mingxun Zhou (Hong Kong University of Science and Technology)
- 3. Haoyu Niu (Fudan University)
- 4. Guopeng Lin (Fudan University)
- 5. Weili Han (Fudan University)
BibTeX Citation
@article{chen_vldb26,
title = {{Bifrost: A Much Simpler Secure Two-Party Data Join Protocol for Secure Data Analytics}},
author = {Chen, Shuyu and Zhou, Mingxun and Niu, Haoyu and Lin, Guopeng and Han, Weili},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {6},
pages = {1156--1169},
doi = {10.14778/3797919.3797925},
url = {https://doi.org/10.14778/3797919.3797925},
year = {2026}
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Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 70 | Privacy-Preserving Data Mining | 2000 | SIGMOD | 0.0003804755 |
| 1,249 | Privacy Preserving Vertical Federated Learning for Tree-based Models | 2020 | VLDB | 0.00011495357 |
| 1,459 | SMCQL: Secure Querying for Federated Databases | 2017 | VLDB | 0.00010717725 |
| 1,998 | A Worst-Case Optimal Multi-Round Algorithm for Parallel Computation of Conjunctive Queries | 2017 | PODS | 9.3363505e-05 |
| 2,045 | Efficient Oblivious Database Joins | 2020 | VLDB | 9.2632279e-05 |
| 3,578 | Advanced Join Strategies for Large-Scale Distributed Computation | 2014 | VLDB | 7.2899943e-05 |
| 5,714 | Hu-Fu: Efficient and Secure Spatial Queries over Data Federation | 2022 | VLDB | 6.1117296e-05 |
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