PRIPEL: Privacy-Preserving Event Log Publishing Including Contextual Information
This addresses privacy concerns for individuals in business process analysis, though it is incremental by focusing on case-level privacy instead of log-level.
The paper tackles the problem of preserving privacy in event log publishing while retaining contextual information, which existing methods neglect, and demonstrates the feasibility of the PRIPEL framework in a real-world case study.
Event logs capture the execution of business processes in terms of executed activities and their execution context. Since logs contain potentially sensitive information about the individuals involved in the process, they should be pre-processed before being published to preserve the individuals' privacy. However, existing techniques for such pre-processing are limited to a process' control-flow and neglect contextual information, such as attribute values and durations. This thus precludes any form of process analysis that involves contextual factors. To bridge this gap, we introduce PRIPEL, a framework for privacy-aware event log publishing. Compared to existing work, PRIPEL takes a fundamentally different angle and ensures privacy on the level of individual cases instead of the complete log. This way, contextual information as well as the long tail process behaviour are preserved, which enables the application of a rich set of process analysis techniques. We demonstrate the feasibility of our framework in a case study with a real-world event log.