Hu-Fu: Efficient and Secure Spatial Queries over Data Federation
Summary: Hu-Fu: first efficient secure spatial query system for data federations, pushing most work to plaintext and using few dedicated secure operators. It supports SQL and heterogeneous backends; experiments show improved runtime and reduced communication. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Yongxin Tong (Beihang University)
- 2. Xuchen Pan (Beihang University)
- 3. Yuxiang Zeng (Hong Kong University of Science and Technology)
- 4. Yexuan Shi (Beihang University)
- 5. Chunbo Xue (Beihang University)
- 6. Zimu Zhou (Singapore Management University)
- 7. Xiaofei Zhang (University of Memphis)
- 8. Lei Chen (Hong Kong University of Science and Technology)
- 9. Yi Xu (Beihang University)
- 10. Ke Xu (Beihang University)
- 11. Weifeng Lv (Beihang University)
BibTeX Citation
@article{tong_vldb22,
title = {{Hu-Fu: Efficient and Secure Spatial Queries over Data Federation}},
author = {Tong, Yongxin and Pan, Xuchen and Zeng, Yuxiang and Shi, Yexuan and Xue, Chunbo and Zhou, Zimu and Zhang, Xiaofei and Chen, Lei and Xu, Yi and Xu, Ke and Lv, Weifeng},
journal = {PVLDB},
series = {{VLDB} '22},
volume = {15},
number = {6},
pages = {1159--1172},
doi = {10.14778/3514061.3514064},
url = {https://doi.org/10.14778/3514061.3514064},
year = {2022}
}Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,906 | FedKNN: Secure Federated k-Nearest Neighbor Search | 2024 | SIGMOD | 7.0287643e-05 |
| 4,785 | Data-Sharing Markets: Model, Protocol, and Algorithms to Incentivize the Formation of Data-Sharing Consortia | 2023 | SIGMOD | 6.5084717e-05 |
| 6,810 | FedSQ: A Secure System for Federated Vector Similarity Queries | 2024 | VLDB | 5.766208e-05 |
| 9,201 | Hu-Fu: A Data Federation System for Secure Spatial Queries | 2022 | VLDB | 5.3058708e-05 |
| 10,519 | Bifrost: A Much Simpler Secure Two-Party Data Join Protocol for Secure Data Analytics | 2026 | VLDB | 5.093636e-05 |
| 10,685 | U-DPAP: Utility-aware Efficient Range Counting on Privacy-preserving Spatial Data Federation | 2025 | SIGMOD | 5.093636e-05 |
| 11,046 | FedVSE: A Privacy-Preserving and Efficient Vector Search Engine for Federated Databases | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 5,395 | AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data | 2015 | VLDB |
| 2 | 4,480 | LocationSpark: A Distributed In-Memory Data Management System for Big Spatial Data | 2016 | VLDB |
| 3 | 12,141 | A Demonstration of AQWA: Adaptive Query-Workload-Aware Partitioning of Big Spatial Data | 2015 | VLDB |
| 4 | 1,984 | Shrinkwrap: Efficient SQL Query Processing in Differentially Private Data Federations | 2019 | VLDB |
| 5 | 6,810 | FedSQ: A Secure System for Federated Vector Similarity Queries | 2024 | VLDB |
| 6 | 9,716 | Querying Shared Data with Security Heterogeneity | 2020 | SIGMOD |
| 7 | 10,685 | U-DPAP: Utility-aware Efficient Range Counting on Privacy-preserving Spatial Data Federation | 2025 | SIGMOD |
| 8 | 1,067 | Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce | 2013 | VLDB |
| 9 | 1,459 | SMCQL: Secure Querying for Federated Databases | 2017 | VLDB |
| 10 | 9,201 | Hu-Fu: A Data Federation System for Secure Spatial Queries | 2022 | VLDB |