Detection of anomalous actions in the network based on machine learning

Публікація:
Detection of anomalous actions in the network based on machine learning

dc.contributor.author	Kulia, V.
dc.contributor.author	Petrenko, O.
dc.date.accessioned	2025-02-25T17:07:45Z
dc.date.available	2025-02-25T17:07:45Z
dc.date.issued	2024
dc.description.abstract	As cyber threats become more sophisticated, the need for effective anomaly detection systems has never been more critical. The usage of machine learning techniques to detect anomalous behavior in network traffic in comparison with traditional detection methods has been researched in this paper. Key challenges, benefits, and real-world applications of machine learning in this area were discussed.
dc.identifier.citation	Kulia V. Detection of anomalous actions in the network based on machine learning / V. Kulia, O. Petrenko // Computer and information systems and technologies : Seventh International Scientific and Technical Conference, 2024. – Kharkiv : NURE, 2024. – p. 40-41.
dc.identifier.issn	2710-463X
dc.identifier.uri	https://openarchive.nure.ua/handle/document/29847
dc.language.iso	en
dc.rights	Attribution-NonCommercial-NoDerivatives 4.0 International	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject	Anomaly Detection
dc.subject	Machine Learning
dc.subject	Network Security
dc.subject	Cybersecurity
dc.subject	Intrusion Detection Systems (IDS)
dc.subject	Semi- Supervised Learning
dc.title	Detection of anomalous actions in the network based on machine learning
dc.type	Thesis
dspace.entity.type	Publication