Poster: Towards Pattern-Level Privacy Protection in Distributed Complex Event Processing

Open Access
Authors
Publication date 2023
Book title DEBS 2023
Book subtitle proceedings of the 17th ACM International Conference on Distributed and Event-based Systems : June 27-30, 2023, Neuchâtel, Switzerland
ISBN (electronic)
  • 9798400701221
Event 17th ACM International Conference on Distributed and Event-based Systems, DEBS 2023
Pages (from-to) 185-186
Number of pages 2
Publisher New York, NY: Association for Computing Machinery
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
Abstract

In event processing systems, detected event patterns can reveal privacy-sensitive information. In this paper, we propose and discuss how to integrate pattern-level privacy protection in event-based systems. Compared to state-of-the-art approaches, we aim to enforce privacy independent of the particularities of specific operators. We accomplish this by supporting the flexible integration of multiple obfuscation techniques and studying deployment strategies for privacy-enforcing mechanisms. In addition, we share ideas on how to model the adversary's knowledge to select appropriate obfuscation techniques for the discussed deployment strategies. Initial results indicate that flexibly choosing obfuscation techniques and deployment strategies is essential to conceal privacy-sensitive event patterns accurately.

Document type Conference contribution
Language English
Published at https://doi.org/10.1145/3583678.3603278
Other links https://www.scopus.com/pages/publications/85170054108
Downloads
3583678.3603278 (Final published version)
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