An Efficient and Secure Blockchain Consensus Protocol for Internet of Vehicles

Abstract

Conventional blockchain consensus protocols tailored for the Internet of Vehicles (IoV) usually face low transaction throughput, high latency, and elevated communication overhead issues. To address these issues, in this paper, we propose ESBCP, an efficient and secure blockchain consensus protocol for the IoV environment. Firstly, considering the significant performance differences among nodes in the IoV, we designed a blockchain consensus model for the IoV. Roadside units execute a trust evaluation mechanism to select high-quality vehicle nodes for the consensus process, thereby reducing the likelihood of malicious nodes in the consensus cluster. Secondly, we designed a node partition strategy to adapt to the dynamic feature of the IoV. Finally, addressing the mobility of nodes in the IoV, we introduced a dynamic unique node list. Vehicle nodes can promptly select nodes with high reliability from the list of communicable nodes to join their unique node list, while also promptly removing nodes with low reliability from their unique node list. Combining these strategies, we propose DK-PBFT, an improved Practical Byzantine Fault Tolerance consensus algorithm. The algorithm meets the efficiency and mobility requirements of vehicular networks. Through theoretical analysis, ESBCP could prevent external and internal security risks while reducing communication overhead. Experimental verification demonstrated that ESBCP effectively reduces consensus latency and improves transaction throughput. Our proposed ESBCP can be used in other application scenarios that require high consensus efficiency.

BOppCL: Blockchain-Enabled Opportunistic Federated Learning Applied in Intelligent Transportation Systems

“…Blockchain-based federated learning (BCFL) [35] is seen as a novel data-sharing model in edge networks of the Internet of Things (IoT), due to its decentralization, collaborative model training, and privacy protection benefits. When comparing existing research schemes in the context of ITS, it becomes clear that many of the data-sharing approaches overlook the critical aspects of user incentives and consensus algorithms and their impact on system efficiency [36]. Additionally, the aggregation methods used in these schemes play an important role in determining the effectiveness and efficiency of the sharing mechanisms.…”