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Authors: Helmut Neuschmied 1 ; Martin Winter 1 ; Katharina Hofer-Schmitz 1 ; Branka Stojanovic 1 and Ulrike Kleb 2

Affiliations: 1 DIGITAL – Institute for Information and Communication Technologies, Joanneum Research GesmbH, Graz, Austria ; 2 POLICIES – Institute for Economic and Innovation Research, Joanneum Research GesmbH, Graz, Austria

Keyword(s): Autoencoder, Deep Learning, Anomaly Detection, Network Intrusion Detection, Variational Autoencoder.

Abstract: Network intrusion detection is one of the most import tasks in today’s cyber-security defence applications. In the field of unsupervised learning methods, variants of variational autoencoders promise good results. The fact that these methods are very computationally time-consuming is hardly considered in the literature. Therefore, we propose a new two-stage approach combining a fast preprocessing or filtering method with a variational autoencoder using reconstruction probability. We investigate several types of anomaly detection methods mainly based on autoencoders to select a pre-filtering method and to evaluate the performance of our concept on two well established datasets.

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Paper citation in several formats:
Neuschmied, H.; Winter, M.; Hofer-Schmitz, K.; Stojanovic, B. and Kleb, U. (2021). Two Stage Anomaly Detection for Network Intrusion Detection. In Proceedings of the 7th International Conference on Information Systems Security and Privacy - ICISSP; ISBN 978-989-758-491-6; ISSN 2184-4356, SciTePress, pages 450-457. DOI: 10.5220/0010233404500457

@conference{icissp21,
author={Helmut Neuschmied. and Martin Winter. and Katharina Hofer{-}Schmitz. and Branka Stojanovic. and Ulrike Kleb.},
title={Two Stage Anomaly Detection for Network Intrusion Detection},
booktitle={Proceedings of the 7th International Conference on Information Systems Security and Privacy - ICISSP},
year={2021},
pages={450-457},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010233404500457},
isbn={978-989-758-491-6},
issn={2184-4356},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Information Systems Security and Privacy - ICISSP
TI - Two Stage Anomaly Detection for Network Intrusion Detection
SN - 978-989-758-491-6
IS - 2184-4356
AU - Neuschmied, H.
AU - Winter, M.
AU - Hofer-Schmitz, K.
AU - Stojanovic, B.
AU - Kleb, U.
PY - 2021
SP - 450
EP - 457
DO - 10.5220/0010233404500457
PB - SciTePress

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