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A Trust Based False Message Detection Model for Multi-Unmanned Aerial Vehicle Network

Unmanned Aerial Vehicles (UAVs) are increasing in number all over the world as they are very useful as well as effective for the society. UAVs are commonly known as drones, which are being used by different sectors like military, commercial, scientific, recreational, and many more. In order to perform different tasks and responsibilities, communication is considered as an important aspect. A multi-UAV network exchanges real-time messages using UAV-to-UAV (U2U) communication and UAV-to-Infrastructure (U2I) communication. However, a false message will impact navigation, monitoring, and tracking of other drones. In this paper, an event-based reputation model is proposed to filter false event messages. This solution considers two different roles for the same event. A dynamic role-development, reputation, and evaluation mechanism is determined, whether an incoming message is true and trustworthy to other UAVs. By using this, the spreading of false event messages can be prevented in multi-UAV network. Simulation results show that this model performs better in filtering the false event messages.