An Intelligent Network Intrusion Detection Framework for Reliable UAV-Based Communication

The recent introduction of unmanned aerial vehicles (UAVs) sectors has proven to be highly promising in fields like agricultural, medical, industrial automation, remote monitoring, and military applications. For data collection from other linked Internet of Things (IoT)-based devices and for easing communication within the UAV network, the UAVs heavily rely on wireless communication protocols. They are vulnerable to attacks because of the issues brought on by remote operations and reliance on wireless protocols. In order to identify and isolate threats, it is important to design an intrusion detection system (IDS) for UAVs. In accordance with this perspective, the work presented in this article is concentrated on developing an intelligent framework for anomaly detection in UAV networks. The effectiveness of the suggested model with respect to various performance measures, such as precision, recall, F-measure, prediction accuracy, and CPU time, is empirically demonstrated using real-world UAV data. The proposed model was found to perform better than base models by offering an accuracy of 99.372.