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FCTM: A Novel Fuzzy Classification Trust Model for Enhancing Reliability in Flying Ad Hoc Networks (FANETs)
Kuldeep Singh and Anil Kumar Verma

Worldwide researchers have immensely contributed in the area of ad hoc networks. Lately, there is an extension to these networks, using Unmanned Aerial Vehicles (UAVs) as a mobile network node(s), popularly known as Flying Ad hoc Networks (FANETs). The foremost ability –fly, of these networks makes them viable for tactical as well as civilian operations. Looking into their characteristics, environment, and applications, security is an essential aspect. During the mission, the nodes collaborate and cooperate. Therefore, trust among the nodes (UAVs) is essential. In this paper, a fuzzy classification trust model (FCTM) for FANETs is presented. The node classification is proposed based on node’s behavior and performance in the network. Further, Quality of Service (QoS) and social parameters are used for evaluating the trust value of each node to segregate the selfish and malicious nodes. A decay function is also considered to replicate the real-world behavior of the UAVs.With the help of experiments, the best trust aggregation weights between QoS and social parameters are identified to classify the network nodes. Also, the classification accuracy of the proposed model is demonstrated. Results indicate that the proposed model, FCTM performs better than existing trust models, COI-HiTrust and AFStrust, in a highly dynamic environment for FANETs.

Keywords: Trust, FANETs, FANETs security, fuzzy classification

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