Blockchain-Based Secure Communication of Intelligent Transportation Digital Twins System

The present work aims to improve the communication security of Internet of Vehicles (IoV) nodes in intelligent transportation through studying the safety of IoV in smart transportation based on Blockchain (BC). An IoV DTs model is built by combining big data with Digital Twins (DTs). Then, regarding the current IoV communication security issues, a secure communication architecture for the IoV system is proposed based on the immutable and trackable BC data. Besides, Wasserstein Distance Based Generative Adversarial Network (WaGAN) model constructs the IoV node risk forecast model. Because the WaGAN model calculates the loss function through Wasserstein distance, the learning rate of the model accelerates remarkably. After ten iterations, the loss rate of the WaGAN model is close to zero. Massive in-vehicle devices in IoV are connected simultaneously to the base station, causing network channel congestion. Therefore, a Group Authentication and Privacy-preserving (GAP) scheme is put forward. As users increase during authentication, the GAP scheme performs better than other authentication access schemes. In summary, the Intelligent Transportation System driven by DTs can promote intelligent transportation management. Besides, introducing BC into IoV can improve access control's accuracy and response efficiency. The research reported here has significant value for improving the security of the information sharing of the IoV.

Automated summary

This study aims to improve the communication security of Internet of Vehicles (IoV) nodes in intelligent transportation by studying the safety of IoV in smart transportation based on Blockchain. An IoV DTs model combining big data with Digital Twins (DTs) is built, and a secure communication architecture based on immutable and trackable BC data is proposed to address current IoV communication security issues. Additionally, a WaGAN model based on Wasserstein Distance is utilized to construct an IoV node risk forecast model. Furthermore, a Group Authentication and Privacy-preserving (GAP) scheme is put forward to handle network channel congestion caused by simultaneous connections of in-vehicle devices in IoV. In summary, this research has significant value in improving the security of information sharing in IoV.