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Authors: Marcin Michalak ; Łukasz Wawrowski ; Marek Sikora ; Rafał Kurianowicz ; Artur Kozłowski and Andrzej Białas

Affiliation: Research Network Łukasiewicz, Institute of Innovative Technologies EMAG, ul. Leopolda 31, 40–189 Katowice, Poland

Keyword(s): Anomaly Detection, Network Traffic Monitoring, Outlier Analysis, Data Mining.

Abstract: Network traffic monitoring becomes, year by year, an increasingly more important branch of network infrastructure maintenance. There exist many dedicated tools for on-line network traffic monitoring that can defend the typical (and known) types of attacks by blocking some parts of the traffic immediately. However, there may occur some yet unknown risks in network traffic whose statistical description should be reflected as slowin-time changing characteristics. Such non-rapidly changing variable values probably should not be detectable by on–line tools. Still, it is possible to detect these changes with the data mining method. In the paper the popular anomaly detection methods with the application of the moving window procedure are presented as one of the approaches for anomaly (outlier) detection in network traffic monitoring. The paper presents results obtained on the real outer traffic data, collected in the Institute.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Michalak, M., Wawrowski, Ł., Sikora, M., Kurianowicz, R., Kozłowski, A. and Białas, A. (2021). Outlier Detection in Network Traffic Monitoring. In Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM; ISBN 978-989-758-486-2; ISSN 2184-4313, SciTePress, pages 523-530. DOI: 10.5220/0010238205230530

@conference{icpram21,
author={Marcin Michalak and Łukasz Wawrowski and Marek Sikora and Rafał Kurianowicz and Artur Kozłowski and Andrzej Białas},
title={Outlier Detection in Network Traffic Monitoring},
booktitle={Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM},
year={2021},
pages={523-530},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010238205230530},
isbn={978-989-758-486-2},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods - ICPRAM
TI - Outlier Detection in Network Traffic Monitoring
SN - 978-989-758-486-2
IS - 2184-4313
AU - Michalak, M.
AU - Wawrowski, Ł.
AU - Sikora, M.
AU - Kurianowicz, R.
AU - Kozłowski, A.
AU - Białas, A.
PY - 2021
SP - 523
EP - 530
DO - 10.5220/0010238205230530
PB - SciTePress

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