Abstract
Providing security on the internet of battlefield things (IoBT) is a crucial task because of various factors such as heterogeneous, dynamic, and resource-constrained devices. Besides, authentication is essential, and it ensures the initial level of security in the network; therefore, ensuring authentication of various interconnected battlefield sensors/devices is the primary attention for the military applications. With this idea in mind, in this paper, a trust model that uses a decision tree to identify and isolate the misbehaving battlefield thing in the IoBT environment is proposed. The decision tree is the predictive modeling and machine learning technique that provides an accurate estimation for selecting authenticated nodes in IoBT by addressing the rank attack by the way security of IoBT environment can be ensured. The mathematical model shows the applicability of the proposed work. The simulation results show the proposed model is better than the existing routing protocol for low power lossy network (RPL) and the protocol which is similar to the proposed one.
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