Search Results for author: Stephan A. Fahrenkrog-Petersen

Found 4 papers, 3 papers with code

SaCoFa: Semantics-aware Control-flow Anonymization for Process Mining

1 code implementation17 Sep 2021 Stephan A. Fahrenkrog-Petersen, Martin Kabierski, Fabian Rösel, Han van der Aa, Matthias Weidlich

Privacy-preserving process mining enables the analysis of business processes using event logs, while giving guarantees on the protection of sensitive information on process stakeholders.

A Distance Measure for Privacy-preserving Process Mining based on Feature Learning

no code implementations14 Jul 2021 Fabian Rösel, Stephan A. Fahrenkrog-Petersen, Han van der Aa, Matthias Weidlich

To avoid this and incorporate the semantics of activities during anonymization, we propose to instead incorporate a distance measure based on feature learning.

Secure Multi-Party Computation for Inter-Organizational Process Mining

1 code implementation4 Dec 2019 Gamal Elkoumy, Stephan A. Fahrenkrog-Petersen, Marlon Dumas, Peeter Laud, Alisa Pankova, Matthias Weildich

In this setting, this paper proposes an approach for constructing and querying a common type of artifact used for process mining, namely the frequency and time-annotated Directly-Follows Graph (DFG), over multiple event logs belonging to different parties, in such a way that the parties do not share the event logs with each other.

Cryptography and Security

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

1 code implementation23 May 2019 Stephan A. Fahrenkrog-Petersen, Niek Tax, Irene Teinemaa, Marlon Dumas, Massimiliano de Leoni, Fabrizio Maria Maggi, Matthias Weidlich

Predictive process monitoring is a family of techniques to analyze events produced during the execution of a business process in order to predict the future state or the final outcome of running process instances.

Predictive Process Monitoring

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