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：

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

引用

页码：177 / 214

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