APD tool: Mining Anomalous Patterns from Event Logs

Laura Genga, Mahdi Alizadeh, Domenico Potena, Claudia Diamantini, Nicola Zannone

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Title of host publicationProceedings of the Demo Track and Dissertation Award of the 15th International Conference on Business Process Modeling, BPM 2017
EditorsRobert Clarisó, Henrik Leopold , Jan Mendling, Wil van der Aalst, Akhil Kumar, Brian Pentland, Mathias Weske
Place of PublicationAachen
Number of pages5
Publication statusPublished - 2017
Externally publishedYes

Publication series

NameCEUR Workshop Proceedings
ISSN (Electronic)1613-0073

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