PrivNUD: Effective Range Query Processing under Local Differential Privacy-Reference-Cited by-同舟云学术

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PrivNUD: Effective Range Query Processing under Local Differential Privacy

Published:2023-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 39th International Conference on Data Engineering (ICDE)
language:
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Author:

Wang Ning¹,Wang Yaohua¹,Wang Zhigang¹,Nie Jie¹,Wei Zhiqiang¹,Tang Peng²,Gu Yu³,Yu Ge³

Affiliation:

1. Ocean University of China,School of Computer Science and Engineering,China

2. Ministry of Education, Shandong University,Key Lab of Cryptologic Technology and Information Security,China

3. Northeastern University,School of Computer Science and Engineering,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10184508/10184509/10184834.pdf?arnumber=10184834

Reference34 articles.

1. Optimizing error of high-dimensional statistical queries under differential privacy

2. The matrix mechanism: optimizing linear counting queries under differential privacy

3. The IPUMS Project: An Update

4. Answering Multi-Dimensional Analytical Queries under Local Differential Privacy

5. Answering range queries under local differential privacy

Cited by 4 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. PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy;Proceedings of the VLDB Endowment;2024-07

2. A Range Query Scheme for Spatial Data with Shuffled Differential Privacy;Mathematics;2024-06-21

3. Answering Spatial Density Queries Under Local Differential Privacy;IEEE Internet of Things Journal;2024-05-15

4. Local differential privacy and its applications: A comprehensive survey;Computer Standards & Interfaces;2024-04

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