Efficient and Accurate Range Counting on Privacy-Preserving Spatial Data Federation-Reference-Cited by-同舟云学术

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Efficient and Accurate Range Counting on Privacy-Preserving Spatial Data Federation

Published:2023 Issue: Volume: Page:317-333
ISSN:0302-9743
Container-title:Database Systems for Advanced Applications
language:
Short-container-title:

Author:

Li Maocheng^ORCID,Zeng Yuxiang^ORCID,Chen Lei^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-30637-2_21

Reference27 articles.

1. Full paper (2022). https://github.com/csmichael/dpfed/blob/main/full.pdf

2. Andres, M.E., Bordenabe, N.E., Cjhatzikokolakis, K., Palamidessi, C.: Geo-indistinguishability: differential privacy for location-based systems. In: CCS (2013)

3. Bater, J., Elliott, G., Eggen, C., Goel, S., Kho, A.N., Rogers, J.: SMCQL: secure query processing for private data networks. VLDB (2017)

4. Bater, J., He, X., Ehrich, W., Machanavajjhala, A., Rogers, J.: Shrinkwrap: efficient SQL query processing in differentially private data federations. VLDB (2018)

5. Bater, J., Park, Y., He, X., Wang, X., Rogers, J.: SAQE: practical privacy-preserving approximate query processing for data federations. VLDB (2020)

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Federated $k$-Dominant Skyline: An Efficient Approach Under Differential Privacy;2023 5th International Conference on Data-driven Optimization of Complex Systems (DOCS);2023-09-22

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