A Hierarchical Unmanned Aerial Vehicle Network Intrusion Detection and Response Approach Based on Immune Vaccine Distribution

Unmanned Aerial Vehicles (UAVs) have experienced rapid development, permeating diverse domains. However, addressing security challenges in UAV networks remains daunting due to resource limitations and the high autonomy of UAV terminals. The current research on UAV network intrusion detection lacks an efficient process covering each UAV terminal and a lightweight collaborative response mechanism between UAVs and ground stations, which affects the performance of UAV network intrusion detection. In this paper, inspired by the vaccine distribution mechanism in artificial immune systems, we propose a hierarchical UAV network intrusion detection and response approach based on the vaccine distribution. Specifically, we first implement an immune game-based negative selection algorithm at the ground station, to effectively generate vaccines covering the immune space. Then, we distribute vaccines to UAV terminals, empowering them with intrusion detection capabilities. Finally, we introduce a collaborative response mechanism to enable the intrusion detection at UAV terminals and perform terminal state assessments. We evaluate the performance of our proposed approach on a large number of real UAV network datasets. The experimental results indicate that our proposed intrusion detection approach for UAV networks at ground stations surpasses all baseline models. In scenarios involving air-ground coordination, our suggested collaborative response approach proves to be effective in enabling intrusion detection at the UAV terminal, facilitating timely and efficient UAV intrusion detection. Moreover, we demonstrate on the ALFA and NSL-KDD datasets that our approach excels in detecting UAV network intrusions. Particularly, on real UAV network data (ALFA), the detection rate reaches 99.05%, and the accuracy is 96.13%, surpassing other models by approximately 6%. IEEE