Fuzzy logic based social trust computation scheme in Flying Ad-hoc network

The Flying Ad Hoc Networks (FANETs) are becoming more popular in civic security, military, and multipurpose applications. Owing to its wireless nature and infrastructure-less architecture, the network has some additional security concerns that must be resolved before the system performs worse. Noncooperative drones might introduce harmful and erroneous data, reducing the network's trustworthiness and throughput. Therefore, in the context of trust score, a trustworthy inter-UAV data communication can be achieved by creating a malicious node within the network. This paper describes a social trust computation scheme for clustered-based FANET, which utilises a reputable methodology to separate malicious UAVs within FANET. The mathematical analysis yielded by the proposed scheme is based on fuzzy logic, and it exhibits superior performance in terms of reliability for the existing schemes under adverse conditions. The primary goal of this research is to build social trust scores about the member drones within FANET, which will aid in isolating malicious drones and improve more than 70% accuracy in terms of the packet delivery ratio and average delay concerning other existing approaches.