NEURAL NETWORK-POWERED INTRUSION DETECTION SYSTEM

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DC Field	Value	Language
dc.contributor.author	Karišić, Đorđe	-
dc.contributor.author	Čabarkapa, Milan	-
dc.date.accessioned	2024-12-26T11:26:23Z	-
dc.date.available	2024-12-26T11:26:23Z	-
dc.date.issued	2024	-
dc.identifier.isbn	978-86-6461-074-2	en_US
dc.identifier.uri	https://scidar.kg.ac.rs/handle/123456789/21857	-
dc.description.abstract	This paper provides a comprehensive exploration of an approach addressing the dynamic challenges posed by modern cyber threats through the integration of neural networks into intrusion detection systems. The given approach emphasizes the necessity for adaptive defences in the face of ever-evolving threats, which camouflage as normal network traffic. The methodology, meticulously detailed in the paper, defines the importance of constructing such a system that adeptly identifies underlying patterns in the network data.	en_US
dc.language.iso	en	en_US
dc.subject	Neural Networks	en_US
dc.subject	Intrusion Detection Systems	en_US
dc.subject	Cybersecurity	en_US
dc.subject	Machine Learning	en_US
dc.subject	Adaptive Defence Mechanisms	en_US
dc.title	NEURAL NETWORK-POWERED INTRUSION DETECTION SYSTEM	en_US
dc.type	conferenceObject	en_US
dc.description.version	Published	en_US
dc.type.version	PublishedVersion	en_US
dc.source.conference	Proceedings of International Scientific and Professional Conference “ALFATECH “ Smart Cities and modern technologies	en_US
Appears in Collections:	Faculty of Engineering, Kragujevac

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