LDP-IDS: Local Differential Privacy for Infinite Data Streams-Reference-Cited by-同舟云学术

LDP-IDS: Local Differential Privacy for Infinite Data Streams

Published:2022-06-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2022 International Conference on Management of Data
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Author:

Ren Xuebin¹,Shi Liang¹,Yu Weiren²,Yang Shusen¹,Zhao Cong³,Xu Zongben¹

Affiliation:

1. Xi'an Jiaotong University, Xi'an, China

2. University of Warwick, Coventry, United Kingdom

3. Imperial College London, London, United Kingdom

Funder

Natural Science Foundation of Jiangsu Province

China Postdoctoral Science Foundation

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3514221.3526190

Reference51 articles.

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2. Héber H Arcolezi , Jean-Francc ois Couchot , Bechara Al Bouna, and Xiaokui Xiao. 2021 b. Improving the Utility of Locally Differentially Private Protocols for Longitudinal and Multidimensional Frequency Estimates. arXiv preprint arXiv:2111.04636 ( 2021 ). Héber H Arcolezi, Jean-Francc ois Couchot, Bechara Al Bouna, and Xiaokui Xiao. 2021 b. Improving the Utility of Locally Differentially Private Protocols for Longitudinal and Multidimensional Frequency Estimates. arXiv preprint arXiv:2111.04636 (2021).

3. c. Longitudinal Collection and Analysis of Mobile Phone Data with Local Differential Privacy. Privacy and Identity Management: 15th IFIP WG 9.2, 9.6/11.7, 11.6/SIG 9.2. 2 International Summer School, Maribor, Slovenia, September 21--23, 2020;Arcolezi Héber H;Revised Selected Papers,2021

4. Borja Balle , Gilles Barthe , and Marco Gaboardi . 2018 . Privacy amplification by subsampling: tight analyses via couplings and divergences . In Proc. NeurIPS. 6280--6290 . Borja Balle, Gilles Barthe, and Marco Gaboardi. 2018. Privacy amplification by subsampling: tight analyses via couplings and divergences. In Proc. NeurIPS. 6280--6290.

5. CGM

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