Electric vehicle based smart cloud model cyber security analysis using fuzzy machine learning with blockchain technique

Electric vehicles' growing need on in-car and inter-car connection can cause major issues for the infrastructure. By providing a secure and trustworthy intelligent framework, this article will mainly tackle the problem of cyberattacks in electric cars and help to keep them safe from hackers. This paper introduces a novel approach to cyber security analysis that makes use of blockchain technology for smart cloud computing and fuzzy machine learning, both of which are grounded in electric car technology. To monitor and transmit data from electric vehicles, this case employs the smart grid integrated cloud computing model, while to evaluate potentially dangerous actions, the fuzzy adversarial Q-stochastic model (FAQS) is used. Based on kinds of users who have the proper access permissions towards authorized and unauthorized users in accordance with their responsibilities as defined by role-based access control policies, data is encrypted as well as decrypted. A variety of cyber security data sets are subjected to an experimental examination in terms of security rate, RMSE, quality of service, scalability, and energy efficiency. Proposed technique attained energy efficiency 98%, QoS 96%, scalability 91%, security rate 95%.