ELPaaS: Event log privacy as a service

Martin Bauer, Stephan A. Fahrenkrog-Petersen, Agnes Koschmider, Felix Mannhardt, Han van der Aa, Matthias Weidlich

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

6 Citaten (Scopus)

Samenvatting

The privacy of an organization's workers represents a crucial concern in process mining settings, where data on an individual's performance is recorded and possibly shared for analysis. To enable users to appropriately deal with privacy concerns in process mining, this paper introduces ELPaaS (Event Log Privacy as a Service), a web application that offers state-of-the-art techniques for event log sanitization and privacy-preserving process mining queries. By employing our techniques, users obtain event logs and process mining results that provide privacy guarantees such as differential privacy and k-anonymity. Hence, the privacy of an organization's workers is protected.

Originele taal-2Engels
TitelBPMT 2019 BPM 2019 Dissertation Award, Doctoral Consortium, and Demonstration Track
SubtitelProceedings of the Dissertation Award, Doctoral Consortium, and Demonstration Track at BPM 2019 co-located with 17th International Conference on Business Process Management (BPM 2019)
RedacteurenBenoit Depaire, Johannes de Smedt, Marlon Dumas
UitgeverijCEUR-WS.org
Pagina's159-163
StatusGepubliceerd - 2019
Evenement2019 Dissertation Award, Doctoral Consortium, and Demonstration Track at BPM, BPMT 2019 - Vienna, Oostenrijk
Duur: 1 sep 20196 sep 2019

Publicatie series

NaamCEUR Workshop Proceedings
UitgeverijCEUR-WS.org
Volume2420
ISSN van geprinte versie1613-0073

Congres

Congres2019 Dissertation Award, Doctoral Consortium, and Demonstration Track at BPM, BPMT 2019
Land/RegioOostenrijk
StadVienna
Periode1/09/196/09/19

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