A Scheme for Detecting Malicious Nodes in UAV Clusters Based on Community Division

Abstract

With the wide use of UAV clusters, malicious attacks against UAV nodes are becoming more and more frequent. Aiming at the problem of malicious node detection in large-scale UAV clusters, this paper proposes a malicious node detection scheme based on community division. Firstly, the Leiden community discovery algorithm divides the flight cluster into multiple communities. Then, this paper presents a combined node importance evaluation algorithm using UAV Communication topology and control topology to evaluate the importance of cluster nodes. Finally, this paper proposes a method to select community leader nodes by using the importance, trust degree and residual power of UAV community nodes.