Detection of nodes disseminating false data is a prerequisite for effective deployment of
Internet of Vehicles (IoV) services. This work proposed a novel hyper-tuned ensemble
Random Forest (Ens. RF) algorithm to detect false basic safety messages in IoV.
Performance evaluation was done using the Vehicular Reference Misbehavior (VeReMi)
dataset comprising data-centric misbehavior evaluation for vehicular networks. For
validation, a comparative analysis of the performance of the proposed “Ens. RF” model, five …