A Trust Model for Effective Cooperation in Flying Ad Hoc Networks Using Genetic Algorithm

Abstract

The advancement of automated systems and their capabilities encourage the use of unmanned aerial vehicles (UAVs) to form ad hoc networks. Multi-UAV ad hoc networks are efficient and promising to complete the task, especially for perilous missions. A multi-UAV ad hoc network is also known as Flying Ad hoc Networks (FANETs). There are various issues required to be addressed before the effective use of UAVs to form a stable and reliable network. As UAVs collaborate and coordinate with each other to complete the mission, trust among the nodes (UAVs) is a crucial aspect. In this paper, a novel trust model has been proposed where the genetic algorithm is used to optimize the weights of various parameters to evaluate the direct trust values. Direct trust is aggregated with are commendation to compute final trust value of a node. Further, nodes are classified into various clusters and trust values of uncertain nodes undergo risk assessment. Based on risk assessment, nodes are included in the recommendation or discard list. Hence, malicious nodes are segregated from the network using the discard list. The experimental results show that the proposed model has better adaptability and accuracy to be considered for FANETs. More importantly, the proposed model achieves significant performance improvement too.