Privacy and Confidentiality in Process Mining -- Threats and Research Challenges
arXiv:2106.00388 · doi:10.1145/3468877
Abstract
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 foundation for future research on privacy-preserving and confidential process mining techniques. Main threats are identified and related to an 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.
arXiv commentAccepted for publication in ACM Transactions on Management Information Systems
References in corpus (6)
- Technical Privacy Metrics: a Systematic Survey
- Predictive Monitoring of Business Processes
- Differential Privacy: An Economic Method for Choosing Epsilon
- Towards Formalizing the GDPR's Notion of Singling Out
- Quantifying the Re-identification Risk of Event Logs for Process Mining
- Privacy-Preserving Data Publishing in Process Mining