A Reputation Deterministic Framework for True Event Detection in Unmanned Aerial Vehicle Network (UAVN)

UAVs have enormous application possibilities in Internet of Things (IoTs). UAVs provide IoT services to the users by using its sensors, cameras, GPS receivers, etc. for various applications like event detection, military, security, medicine, and surveillance. These services need trusted and reliable communication among the nodes. UAVs have a dynamic and distributed architecture because of which they are prone to malicious attacks. Two factors that provide basic security and control to network traffic congestion and network filter are trust and reputation. In this paper, a reputation management framework is proposed. This framework presents a message-node model which checks the realness of event messages generated in a network after encountering an event, and it also checks the genuineness of the UAV node which reports the event message. This model uses majority voting protocol for determining the truthfulness of event messages. Based on that, reputation is calculated for a message producer. A central hub is introduced which keeps record of all the UAV nodes. Reputation from different recommenders and a global reputation value is used to calculate the node's recommendation bound reputation. Simulation results show that proposed model outperforms the similarity mining model in terms of reputation value analysis.