Anomaly Detection in IoT

The study benchmarks neural networks, Gaussian naive Bayes, support vector machines, and decision trees on generated IoT datasets against KDDCUP99. Feature selection distills only five key attributes, cutting execution time while enhancing accuracy. An improved CNNwGFC model further elevates classification effectiveness on UNSW-NB15.