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...

Full description

Bibliographic Details

Published in:	Wireless communications and mobile computing Vol. 2021; no. 1
Main Authors:	Xie, Bin, Dong, Xinyu, Wang, Changguang
Format:	Journal Article
Language:	English
Published:	Oxford Hindawi 2021 John Wiley & Sons, Inc
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!