Cryptanalysis of the Authentication Schemes and Enhancement for Digital Twin System

Abstract

The rapid development of autonomous vehicle technology has generated a plethora of intelligent services and applications. However, real-time perception, computation and communication related challenges often result in increased latency and degraded user experience. To address these problems, a new computing architecture based on Digital Twin technology is proposed in this research that leverages cloud computing to efficiently collect, integrate, and process the information generated by autonomous vehicles.
The proposed framework offers continuous feedback through real-time synchronization between the physical autonomous vehicles and their corresponding digital twins hosted in the cloud. As the data exchange is happening over open communication networks, it is of critical importance to have strong security, privacy preservation and communication reliability. Therefore, this work aims at designing a secure framework to enable trustworthy data sharing between autonomous vehicles and their digital twins.
The proposed scheme is evaluated through a thorough security analysis to determine its effectiveness. The comparative results show that the proposed methodology reduces the computational and communication overheads significantly compared to the existing vehicle communication approaches and it is well suited for digital twin-enabled transportation environments. The framework lowers communication costs, improves security and privacy, thereby enhancing the overall user experience and boosting operational efficiency. The results of this research are expected to provide significant inputs to the progress of autonomous vehicle technologies and help their smooth integration in future intelligent transportation systems and daily life.