A hybrid model clusters Bot-IoT training data into three traffic profiles with K-Means and assigns the best-performing classifier from Decision Tree, KNN, and XGBoost to each cluster, reporting improved anomaly detection accuracy.
A survey of machine and deep learning methods for internet of things (iot) security
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A Hybrid Cluster-Based Classification Model for Anomaly Detection in Unbalanced IoT Networks
A hybrid model clusters Bot-IoT training data into three traffic profiles with K-Means and assigns the best-performing classifier from Decision Tree, KNN, and XGBoost to each cluster, reporting improved anomaly detection accuracy.