Differential Privacy for Protecting Private Patterns in Data Streams-Reference-Cited by-同舟云学术

Differential Privacy for Protecting Private Patterns in Data Streams

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

Gu He¹,Plagemann Thomas¹,Benndorf Maik¹,Goebel Vera¹,Koldehofe Boris²

Affiliation:

1. University of Olso,Department of Informatics,Oslo,Norway

2. University of Groningen,Bernoulli Institute,Groningen,The Netherlands

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10148090/10148105/10148219.pdf?arnumber=10148219

Reference16 articles.

1. THE EUROPEAN PARLIAMENT AND THE COUNCIL OF THE EUROPEAN UNION Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing Directive 95/46/EC (General Data Protection Regulation);Official Journal of the European Union,0

2. Protecting Spatiotemporal Event Privacy in Continuous Location-Based Services

3. Driving with knowledge from the physical world

4. The algorithmic foundations of differential privacy;dwork;Foundations and Trends� in Theoretical Computer Science,2014

5. Landmark Privacy: Configurable Differential Privacy Protection for Time Series

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1. Towards Guaranteed Privacy in Stream Processing: Differential Privacy for Private Pattern Protection;Proceedings of the 17th ACM International Conference on Distributed and Event-based Systems;2023-06-27