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Abstract
The privacy of an organization’s workers represents a crucial concern in process mining settings, where data on an individual’s performance is recorded and possibly shared for analysis. To enable users to appropriately deal with privacy concerns in process mining, this paper introduces ELPaaS (Event Log Privacy as a Service), a web application that offers state-of-the-art techniques for event log sanitization and privacy-preserving process mining queries. By employing our techniques, users obtain event logs and process mining results that provide privacy guarantees such as differential privacy and k-anonymity. Hence, the privacy of an organization’s workers is protected.