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Stephan A. Fahrenkrog-Petersen

Researcher at Humboldt University of Berlin

Publications -  27
Citations -  323

Stephan A. Fahrenkrog-Petersen is an academic researcher from Humboldt University of Berlin. The author has contributed to research in topics: Process mining & Event (computing). The author has an hindex of 7, co-authored 18 publications receiving 150 citations. Previous affiliations of Stephan A. Fahrenkrog-Petersen include University of Tartu & Technical University of Berlin.

Papers
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Proceedings ArticleDOI

PRETSA: Event Log Sanitization for Privacy-aware Process Discovery

TL;DR: PRETSA is introduced, a novel algorithm for event log sanitization that provides privacy guarantees in terms of k-anonymity and t-closeness and yields event logs of higher utility compared to methods that exploit frequency-based filtering, while providing the same privacy guarantees.
Book ChapterDOI

PRIPEL: Privacy-Preserving Event Log Publishing Including Contextual Information

TL;DR: PRIPEL is introduced, a framework for privacy-aware event log publishing that takes a fundamentally different angle and ensures privacy on the level of individual cases instead of the complete log, which enables the application of a rich set of process analysis techniques.
Posted Content

Fire Now, Fire Later: Alarm-Based Systems for Prescriptive Process Monitoring.

TL;DR: A framework for prescriptive process monitoring is proposed, which extends predictive monitoring with the ability to generate alarms that trigger interventions to prevent an undesired outcome or mitigate its effect and incorporates a parameterized cost model to assess the cost–benefit trade-off of generating alarms.
Book ChapterDOI

Quantifying the Re-identification Risk of Event Logs for Process Mining

TL;DR: In this paper, the authors quantify the risk of re-identification attacks with measures for the individual uniqueness in event logs and report on a large-scale study that explored the individualiqueness in a collection of publicly available event logs.
Journal ArticleDOI

Privacy and Confidentiality in Process Mining: Threats and Research Challenges

TL;DR: In this paper, the authors provide a foundation for future research in process mining with respect to privacy and confidentiality requirements, which are very important prerequisites for applying process mining to comply with regulations and keep company secrets.