APD tool: Mining anomalous patterns from event logs

L. Genga, M. Alizadeh, D. Potena, C. Diamantini, Nicola Zannone

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
70 Downloads (Pure)

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.

Original languageEnglish
Title of host publicationProceedings of the BPM Demo Track and BPM Dissertation Award
EditorsR. Clarisó, H. Leopold, J. Mendling, W. van der Aalst, A. Kumar, B. Pentland, M. Weske
PublisherSun SITE Central Europe
Number of pages5
Publication statusPublished - 2017
Event15th International Conference on Business Process Management (BPM 2017) - Barcelona, Spain
Duration: 10 Sep 201715 Sep 2017
Conference number: 15
https://bpm2017.cs.upc.edu/

Publication series

NameCEUR workshop proceedings
Volume1920
ISSN (Electronic)1613-0073

Conference

Conference15th International Conference on Business Process Management (BPM 2017)
Abbreviated titleBPM 2017
Country/TerritorySpain
CityBarcelona
Period10/09/1715/09/17
Internet address

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