Towards a Standard Feature Set for Network Intrusion Detection System Datasets

Network Intrusion Detection Systems (NIDSs) are important tools for the protection of computer networks against increasingly frequent and sophisticated cyber attacks. Recently, a lot of research effort has been dedicated to the development of Machine Learning (ML) based NIDSs. As in any ML-based app...

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Veröffentlicht in:	Mobile networks and applications Jg. 27; H. 1; S. 357 - 370
Hauptverfasser:	Sarhan, Mohanad, Layeghy, Siamak, Portmann, Marius
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.02.2022 Springer Nature B.V
Schlagworte:	Classification Classifiers Communications Engineering Communications traffic Computer Communication Networks Computer networks Cybersecurity Datasets Electrical Engineering Engineering Intrusion detection systems IT in Business Machine learning Networks Proprietary NetFlow Network intrusion detection system Machine learning
ISSN:	1383-469X, 1572-8153
Online-Zugang:	Volltext
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