Search Results for author:
Found 4 papers, 3 papers with code
SaCoFa: Semantics-aware Control-flow Anonymization for Process Mining
Privacy-preserving process mining enables the analysis of business processes using event logs, while giving guarantees on the protection of sensitive information on process stakeholders.
A Distance Measure for Privacy-preserving Process Mining based on Feature Learning
To avoid this and incorporate the semantics of activities during anonymization, we propose to instead incorporate a distance measure based on feature learning.
Secure Multi-Party Computation for Inter-Organizational Process Mining
In this setting, this paper proposes an approach for constructing and querying a common type of artifact used for process mining, namely the frequency and time-annotated Directly-Follows Graph (DFG), over multiple event logs belonging to different parties, in such a way that the parties do not share the event logs with each other.
Cryptography and Security
Fire Now, Fire Later: Alarm-Based Systems for Prescriptive Process Monitoring
Predictive process monitoring is a family of techniques to analyze events produced during the execution of a business process in order to predict the future state or the final outcome of running process instances.
