An Improved K-Means Clustering Intrusion Detection Algorithm for Wireless Networks Based on Federated Learning

The existing wireless network intrusion detection algorithms based on supervised learning confront many challenges, such as high false detection rate, difficulty in finding unknown attack behaviors, and high cost in obtaining labeled training data sets. This paper presents an improved k-means cluste...

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Vydáno v:	Wireless communications and mobile computing Ročník 2021; číslo 1
Hlavní autoři:	Xie, Bin, Dong, Xinyu, Wang, Changguang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Hindawi 2021 John Wiley & Sons, Inc
Témata:	Algorithms Behavior Cluster analysis Clustering Datasets Federated learning Intrusion detection systems Machine learning Principal components analysis Privacy Vector quantization Wireless networks
ISSN:	1530-8669, 1530-8677
On-line přístup:	Získat plný text
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