Privacy‐preserving authentication scheme for digital twin‐enabled autonomous vehicle environments

Abstract

Abstract Currently, the automotive industry has entered a period of considerable advancement, shifting towards the development of safe, comfortable, and connected autonomous vehicles. However, the need for real‐time sensing, computation, and communication may lead to information overflow in autonomous cars, resulting in data redundancy. Furthermore, anticipating traffic conditions beyond a vehicle's field of view can be quite difficult owing to the restricted range of communication systems. To solve these problems, digital twin systems have been developed for autonomous driving environments. Because autonomous vehicles are driven on open public road networks, this function may jeopardize vehicles, user‐identifying information, and sensitive data. Hence, an authentication scheme that can be deployed in digital‐twin‐enabled autonomous vehicle environments is needed. In this study, we propose a privacy‐preserving authentication mechanism. To establish the security of the proposed method, we performed a formal security analysis based on the real‐or‐random model. Furthermore, we assessed the performance of the proposed scheme, and our results demonstrate that it can reduce calculation and transmission costs.