Towards Pattern-Level Privacy Protection in Distributed Complex Event Processing

Majid Lotfian Delouee, Boris Koldehofe, Viktoriya Degeler

OnderzoeksoutputAcademicpeer review

1 Citaat (Scopus)
98 Downloads (Pure)

Samenvatting

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. Moreover, we share ideas on how to model the adversary’s knowledge to better 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.
Originele taal-2English
TitelProceedings of the 17th ACM International Conference on Distributed and Event-based Systems
SubtitelDEBS '23
UitgeverijACM Press
Pagina's185-186
Aantal pagina's2
ISBN van geprinte versie979-8-4007-0122-1
DOI's
StatusPublished - jun.-2023
EvenementThe 17th ACM International Conference on Distributed and Event-Based Systems (DEBS'23) - University of Neuchatel, Neuchatel, Switzerland
Duur: 27-jun.-202330-jun.-2023
https://2023.debs.org/

Conference

ConferenceThe 17th ACM International Conference on Distributed and Event-Based Systems (DEBS'23)
Land/RegioSwitzerland
StadNeuchatel
Periode27/06/202330/06/2023
Internet adres

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