A main challenge of today’s organizations is the monitoring of their processes to check whether these processes comply with process models specifying the prescribed behavior. Deviations from the prescribed behavior can represent either legitimate work practices not described by the models, which highlight the need of improving it to better reflect the reality, or malicious behaviors representing, for instance, security breaches and frauds. In this paper, we present a tool designed to extract anomalous patterns representing recurrent deviations, together with their correlations, from historical logging data. The tool is targeted to researchers and practitioners in business process and security domains, with background in process mining

APD tool: Mining Anomalous Patterns from Event Logs / Genga, Laura; Alizadeh, Mahdi; Potena, Domenico; Diamantini, Claudia; Zannone, Nicola. - 1920:(2017). (Intervento presentato al convegno 15th International Conference on Business Process Management (BPM 2017) tenutosi a Barcelona, Spain nel September 10-15, 2017).

APD tool: Mining Anomalous Patterns from Event Logs

POTENA, Domenico;DIAMANTINI, Claudia;
2017-01-01

Abstract

A main challenge of today’s organizations is the monitoring of their processes to check whether these processes comply with process models specifying the prescribed behavior. Deviations from the prescribed behavior can represent either legitimate work practices not described by the models, which highlight the need of improving it to better reflect the reality, or malicious behaviors representing, for instance, security breaches and frauds. In this paper, we present a tool designed to extract anomalous patterns representing recurrent deviations, together with their correlations, from historical logging data. The tool is targeted to researchers and practitioners in business process and security domains, with background in process mining
2017
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/250783
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