45 citations · 91 across the 17 of their papers we have counts for
5 papers · 1 filter
The Impact of Event Data Partitioning on Privacy-aware Process Discovery
Jungeun Lim, Stephan A. Fahrenkrog-Petersen, Xixi Lu +2
Information systems support the execution of business processes. The event logs of these executions generally contain sensitive information about customers, patients, and employees…
A Distance Measure for Privacy-preserving Process Mining based on Feature Learning
Fabian Rösel, Stephan A. Fahrenkrog-Petersen, Han van der Aa +1
To enable process analysis based on an event log without compromising the privacy of individuals involved in process execution, a log may be anonymized. Such anonymization strives…
Privacy and Confidentiality in Process Mining -- Threats and Research Challenges
Gamal Elkoumy, Stephan A. Fahrenkrog-Petersen, Mohammadreza Fani Sani +5
Privacy and confidentiality are very important prerequisites for applying process mining in order to comply with regulations and keep company secrets. This paper provides a foundat…
Privacy-aware Process Performance Indicators: Framework and Release Mechanisms
Martin Kabierski, Stephan Fahrenkrog-Petersen, Matthias Weidlich
Process performance indicators (PPIs) are metrics to quantify the degree with which organizational goals defined based on business processes are fulfilled. They exploit the event l…
Secure Multi-Party Computation for Inter-Organizational Process Mining
Gamal Elkoumy, Stephan A. Fahrenkrog-Petersen, Marlon Dumas +3
Process mining is a family of techniques for analysing business processes based on event logs extracted from information systems. Mainstream process mining tools are designed for i…