Detecting Complex Anomalous Behaviors in Business Processes: A Multi-perspective Conformance Checking Approach

In recent years, organizations are putting an increasing emphasis on anomaly detection. Anomalies in business processes can be an indicator of system faults, inefficiencies, or even fraudulent activities. In this paper we introduce an approach for anomaly detection. Our approach considers different perspectives of a business process such as control flow, data and privacy aspects simultaneously.Therefore, it is able to detect complex anomalies in business processes like spurious data processing and misusage of authorizations. The approach has been implemented in the open source ProM framework and its applicability was evaluated through a real-life dataset from a financial organization. The experiment implies that in addition to detecting anomalies of each aspect, our approach can detect more complex anomalies which relate to multiple perspectives of a business process.

Automated summary

In recent years, organizations have been paying more attention to anomaly detection as anomalies in business processes can indicate system faults, inefficiencies, or even fraudulent activities. This paper introduces an approach that considers different perspectives of a business process simultaneously to detect complex anomalies such as spurious data processing and misusage of authorizations. The approach has been implemented in the ProM framework and evaluated using real-life data from a financial organization, showing its ability to detect anomalies related to multiple aspects of a business process.