Privacy and Confidentiality in Process Mining: Threats and Research Challenges

Author:

Elkoumy Gamal1,Fahrenkrog-Petersen Stephan A.2,Sani Mohammadreza Fani3,Koschmider Agnes4,Mannhardt Felix5ORCID,Von Voigt Saskia Nuñez6,Rafiei Majid3,Waldthausen Leopold Von7

Affiliation:

1. University of Tartu, Tartu, Estonia

2. Humboldt-Universität zu Berlin, Berlin, Germany

3. RWTH-Aachen University, Aachen, Germany

4. Kiel University, Kiel, Germany

5. Eindhoven University of Technology, Eindhoven, The Netherlands

6. Technische Universität Berlin, Berlin, Germany

7. Magdalen College, University of Oxford, Oxford, United Kingdom

Abstract

Privacy and confidentiality are very important prerequisites for applying process mining to comply with regulations and keep company secrets. This article provides a foundation for future research on privacy-preserving and confidential process mining techniques. Main threats are identified and related to a motivation application scenario in a hospital context as well as to the current body of work on privacy and confidentiality in process mining. A newly developed conceptual model structures the discussion that existing techniques leave room for improvement. This results in a number of important research challenges that should be addressed by future process mining research.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Management Information Systems

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