Abstract
Internet of things (IoT) connects heterogeneous physical objects to collect the observing data and eases to development of smart transmission systems. Vehicular ad hoc network (VANET) offers many smart services for emerging vehicle-to-vehicle communication systems using sensors. Although, geographical routing solutions have been improved the process of neighbor finding and inter-related vehicle sensors. However, due to the high mobility and realistic environment, reliability and data continuity among data routing are essential for emerging transportation systems. Also, the vehicles are communicating on unrestrained and exposed wireless mediums, thus they are more visible to security threats and compromised data for unauthorized usages. In this paper, we proposed a resilient and secure cooperative intelligent transportation system (RS-ITS) using sensor technologies to optimize route discovery with minimum communication failures. RS-ITS makes use of the roadside unit (RSU) as an intelligent agent using machine learning techniques to predict the finest routes and maintain nominal overheads. It also secures the vehicular network against vulnerabilities and ensures reliable propagation of messages between vehicles and RSUs. The proposed model is tested using simulations for varying data sizes and vehicles, which indicates improved performance for delivery ratio by 17%, data delay by 40%, energy consumption by 22%, routes in-continuity by 17%, network overheads by 27%, and malicious attacks by 43% as compared to other schemes.