Utilising K-Means Clustering and Naive Bayes for IoT Anomaly Detection: A Hybrid Approach

被引:0
|
作者
Best, Lincoln [1 ]
Foo, Ernest [1 ]
Tian, Hui [1 ]
机构
[1] School of Information and Communication Technology, Griffith University, Brisbane,QLD,4111, Australia
来源
Smart Sensors, Measurement and Instrumentation | 2022年 / 43卷
关键词
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I
暂无
中图分类号
学科分类号
摘要
Anomaly detection - Anomaly-detection algorithms - Hybrid approach - K-means - K-means++ clustering - Machine-learning - Multiple devices - Naive bayes - Real-world - Supervised areas
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页码:177 / 214
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