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What is Botnet Detection in Internet of Things Using Stacked Ensemble Learning Model about?

This research presents a novel stacking ensemble learning model, KSDRM, for detecting botnet attacks in Internet of Things (IoT) networks, utilizing various machine learning classifiers and achieving high accuracy rates. The model was trained on the UNSW-NB15 dataset, demonstrating a training accuracy of 99.99% and a testing accuracy of 97.94%. The findings suggest that the KSDRM model effectively enhances cybersecurity measures against evolving botnet threats.

Author

Government Polytechnic

Language

EN