U-DPAP: Utility-aware Efficient Range Counting on Privacy-preserving Spatial Data Federation
Summary: U-DPAP: first DP-only privacy-preserving scheme for range counting in spatial data federations (no SMC). Proposes grouping-based perturbation and representative-silo selection to optimize privacy-utility and efficiency-utility, with formal guarantees and empirical gains. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Yahong Chen
- 2. Xiaoyi Pang
- 3. Xiaoguang Li
- 4. Hanyi Wang
- 5. Ben Niu
- 6. Shengnan Hu
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 83 | Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis | 2009 | SIGMOD | 0.00053933811 |
| 165 | Federated Database Systems for Managing Distributed, Heterogeneous, and Autonomous Databases | 1991 | VLDB | 0.00039502525 |
| 405 | Approximate Query Processing Using Wavelets | 2000 | VLDB | 0.00024057494 |
| 1,261 | Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce | 2013 | VLDB | 0.00012989236 |
| 1,435 | Simba: Efficient In-Memory Spatial Analytics | 2016 | SIGMOD | 0.00012004456 |
| 1,681 | GUPT: Privacy Preserving Data Analysis Made Easy | 2012 | SIGMOD | 0.00010929746 |
| 2,179 | A Framework for Protecting Worker Location Privacy in Spatial Crowdsourcing | 2014 | VLDB | 9.3558219e-05 |
| 2,673 | Shrinkwrap: Efficient SQL Query Processing in Differentially Private Data Federations | 2019 | VLDB | 8.3333418e-05 |
| 5,746 | Hu-Fu: Efficient and Secure Spatial Queries over Data Federation | 2022 | VLDB | 5.3420687e-05 |
| 6,081 | Subgraph Matching over Graph Federation | 2022 | VLDB | 5.2208051e-05 |
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