Improved identification of network anomalies through optimal CURE clustering

In this paper, we propose an advanced network anomaly behavior identification framework to overcome the constraints inherent in conventional rule- or signature-based approaches, which often struggle with emerging and previously unknown threats. Central to our framework is an Enhanced CURE (Cluster U...

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Vydané v:	Engineering Research Express Ročník 6; číslo 4; s. 45217 - 45231
Hlavní autori:	Wu, Xiaoqian, Chen, Cheng, Quan, Lili
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IOP Publishing 01.12.2024
Predmet:	anomaly identification clustering algorithm network anomalous behavior
ISSN:	2631-8695, 2631-8695
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