loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Fábio Bezerra and Jacques Wainer

Affiliation: IC-UNICAMP, Brazil

Keyword(s): Anomaly Detection, Process Mining, Business Process Systems.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: In some domains of application, like software development and health care processes, a normative business process system (e.g. workflow management system) is not appropriate because a flexible support is needed to the participants. On the other hand, while it is important to support flexibility of execution in these domains, security requirements can not be met whether these systems do not offer extra control, which characterizes a trade off between flexibility and security in such domains. This work presents and assesses a set of anomaly detection algorithms in logs of Process Aware Systems (PAS). The detection of an anomalous instance is based on the “noise” which an instance makes in a process model discovered by a process mining algorithm. As a result, a trace that is an anomaly for a discovered model will require more structural changes for this model fit it than a trace that is not an anomaly. Hence, when aggregated to PAS, these methods can support the coexistence of security and flexibility. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.204.65.189

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Bezerra, F. and Wainer, J. (2008). ANOMALY DETECTION ALGORITHMS IN BUSINESS PROCESS LOGS. In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS; ISBN 978-989-8111-37-1; ISSN 2184-4992, SciTePress, pages 11-18. DOI: 10.5220/0001674700110018

@conference{iceis08,
author={Fábio Bezerra. and Jacques Wainer.},
title={ANOMALY DETECTION ALGORITHMS IN BUSINESS PROCESS LOGS},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS},
year={2008},
pages={11-18},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001674700110018},
isbn={978-989-8111-37-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 6: ICEIS
TI - ANOMALY DETECTION ALGORITHMS IN BUSINESS PROCESS LOGS
SN - 978-989-8111-37-1
IS - 2184-4992
AU - Bezerra, F.
AU - Wainer, J.
PY - 2008
SP - 11
EP - 18
DO - 10.5220/0001674700110018
PB - SciTePress