A Trusted Paradigm of Data Management for Blockchain-Enabled Internet of Vehicles in Smart Cities

Abstract

Internet of Vehicles(IoV) enables vehicles to generate and share messages to improve transportation safety and efficiency, especially in a smart city scenario where modern communication technology is utilized. The current IoV, however, faces three main issues: (1) existing frameworks fail to build a complete data management system, (2) received messages in an untrusted environment are challenging to assess for credibility, and (3) the centralized ways to store data are causing severe security and efficiency problems. Blockchain-enabled IoV (BIoV) provides an opportunity for addressing these issues. This paper proposes a trusted paradigm of data management based on a vehicle–road–cloud architecture. A few-shot learning model, Wasserstein Generative Adversarial Network (WGAN) with Synthetic Minority Oversampling Technique (SMOTE) sampling is designed to evaluate whether the uploading message is malicious. This paper also proposes the novel group-weighted-decay Practical Byzantine Fault Tolerance (PBFT) consensus algorithm, an improved version of PBFT to store data, and provides a comprehensive review of its viability and data management procedures. By employing the joint gwd-PBFT and Proof of Trust (PoT) consensus, the method mitigates the issue of excessive incentives. According to simulation results, the system's overall efficiency can be increased while retaining security and availability.