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Detection of Malicious Nodes in UAV-IOT Environment
These days UAV-IOT collaborative environment has become a hot topic for research because UAV adds significant potential to the IoT devices. However, there are multiple issues to address like resource allocation, trajectory optimization energy preservation, selfish and malicious node detection etc. In this article we propose a decision tree based selfish and malicious node detection technique based upon information like residual energy, energy depletion rate, present reputation and credibility of alternative routers. Based on this, next reputation is decided and the node is identified as non-malicious or malicious. During selection of route from clusterhead to a cluster member, malicious nodes are avoided as much as possible, to reduce unnecessary consumption of energy and time.
Keywords
Credit, Energy Efficiency, Malicious, Random Forest, Unmanned Aerial Vehicle.
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