A Novel Secured Multi-Access Edge Computing based VANET with Neuro fuzzy systems based Blockchain Framework

In vehicle ad-hoc networks, the progression of wireless communication technology to 6G, overcomes storage, processing, privacy, and power limits to create an efficient and intelligent next generation transportation system. Vehicular ad hoc network may now offer remarkable availability, reliability, and throughput using 6G technology. However, the VANET system's data should be protected. This paper proposes an effective batch authentication and key exchange technique to avoid contact with hostile vehicle users. Moreover, three types of systems are proposed: PKI, ID-based, and MAC-based. The neuro-fuzzy inference technique was used to predict VANET security ratings. The Homogeneous Discrete-Time Markov Chain model is used to secure data transit. Additionally, this research examined the work from a blockchain perspective combined with MEC. There are 3 level to comprise the architecture: perception, edge computing, and services. Throughout the blockchain transmission process, the first layer make certain the security of VANET data. The perception layer makes use of edge computing and cloud services on the edge. The service layer protects data by using both traditional cloud storage and blockchain technology. The lowest layer of the system architecture is dedicated to the throughput and quality of service requirements of MEC users. The primary challenge is achieving consensus across blockchain nodes while maintaining the MEC system's and blockchain's performance. To simulate the joint optimization problem, a Markov decision process with reward function is utilized. The simulation results are conferred to illustrate the validity of study assertions.