Hu-Fu: A Data Federation System for Secure Spatial Queries
Summary: Hu-Fu is the first data federation system for secure spatial queries, enabling privacy-preserving analytics over cross-owner urban data. It achieves high usability and efficiency by decomposing queries into plaintext operators and minimizing secure operators, demonstrated on cross-company taxi data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Xuchen Pan (Beihang University)
- 2. Yongxin Tong (Beihang University)
- 3. Chunbo Xue (Beihang University)
- 4. Zimu Zhou (Singapore Management University)
- 5. Junping Du (Beijing Institute of Technology)
- 6. Yuxiang Zeng (Hong Kong University of Science and Technology)
- 7. Yexuan Shi (Beihang University)
- 8. Xiaofei Zhang (University of Memphis)
- 9. Lei Chen (Hong Kong University of Science and Technology)
- 10. Yi Xu (Beihang University)
- 11. Ke Xu (Beihang University)
- 12. Weifeng Lv (Beihang University)
BibTeX Citation
@article{pan_vldb22,
title = {{Hu-Fu: A Data Federation System for Secure Spatial Queries}},
author = {Pan, Xuchen and Tong, Yongxin and Xue, Chunbo and Zhou, Zimu and Du, Junping and Zeng, Yuxiang and Shi, Yexuan and Zhang, Xiaofei and Chen, Lei and Xu, Yi and Xu, Ke and Lv, Weifeng},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {12},
pages = {3582--3585},
doi = {10.14778/3554821.3554849},
url = {https://doi.org/10.14778/3554821.3554849},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,810 | FedSQ: A Secure System for Federated Vector Similarity Queries | 2024 | VLDB | 5.766208e-05 |
| 11,422 | TEE-based General-purpose Computational Backend for Secure Delegated Data Processing | 2023 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 182 | Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases | 1991 | VLDB | 0.00026367971 |
| 445 | Apache Calcite: A Foundational Framework for Optimized Query Processing Over Heterogeneous Data Sources | 2018 | SIGMOD | 0.00018336751 |
| 5,714 | Hu-Fu: Efficient and Secure Spatial Queries over Data Federation | 2022 | VLDB | 6.1117296e-05 |
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 6,773 | An Approach For Building Secure Database Federations | 1994 | VLDB |
| 2 | 7,879 | Authenticated Online Data Integration Services | 2015 | SIGMOD |
| 3 | 1,067 | Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce | 2013 | VLDB |
| 4 | 12,141 | A Demonstration of AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data | 2015 | VLDB |
| 5 | 7,605 | High-Performance Geospatial Analytics in HyPerSpace | 2016 | SIGMOD |
| 6 | 1,459 | SMCQL: Secure Querying for Federated Databases | 2017 | VLDB |
| 7 | 9,716 | Querying Shared Data with Security Heterogeneity | 2020 | SIGMOD |
| 8 | 6,810 | FedSQ: A Secure System for Federated Vector Similarity Queries | 2024 | VLDB |
| 9 | 10,685 | U-DPAP: Utility-aware Efficient Range Counting on Privacy-preserving Spatial Data Federation | 2025 | SIGMOD |
| 10 | 5,714 | Hu-Fu: Efficient and Secure Spatial Queries over Data Federation | 2022 | VLDB |