Main Article Content
Cost-effective unmanned aerial vehicles (UAVs) have just developed due to the accelerated spread of wireless communication and networking technologies, and they will soon occupy the majority of our airspace. UAVs can be used to efficiently complete complex missions when organized as an ad hoc network, resulting in the well-known Flying Ad Hoc Networks (FANETs). Furthermore, due to many flight limitations and the highly dynamic topology of FANETs, designing routing protocols is a problematic issue. Previously, we discussed energy-efficient clustering and fuzzy-based route selection for FANET. However, because of the open wireless boundary and the excellent mobility of the drones, FANETs are vulnerable to rogue nodes that might breach the network and pose significant security threats. Trust among the nodes is critical. In this paper, a unique trust method is presented in which the Adaptive Artificial Fish Swarm Strategy (AAFSA) strategy is employed to optimize cluster head (CH) selection. The suggested trust method measures direct trust using improved Bayesian theory and indirect trust using evaluation credibility and activity. ITOPSIS (Improved Technique for Order Performance by Similarity to Ideal Solution) is a new technique for improving the route-finding process. According to the experimental outcomes, the presented method is more adaptable in energy, throughput, delay, overhead, and packet delivery ratio.