【Author】
Chen, Haoyu; Chen, Naiyue; Liu, He; Zhang, Honglei; Xu, Jiabo; Chen, Huaping; Li, Yidong
【Source】PARALLEL AND DISTRIBUTED COMPUTING, APPLICATIONS AND TECHNOLOGIES, PDCAT 2021
【Abstract】Internet of Vehicles (IoV) enables the integration of smart vehicles with Internet and collaborative analysis from shared data among vehicles. Machine learning technologies show significant advantages and efficiency for data analysis in IoV. However, the user data could be sensitive in nature, and the reliability and efficiency of sharing these data is hard to guarantee. Moreover, due to the intermittent and unreliable communications of various distributed vehicles, the traditional machine learning algorithms are not suitable for heterogeneous IoV network. In this paper, we propose a novel reputation mechanism framework that integrates the IoV with blockchain and federated learning named RepBFL. In this framework, blockchain is used to protect the shared data between the vehicles. The Road Side Units (RSU) select the high reputation vehicular nodes to share their data for federated learning. To enhance the security and reliability of the data sharing process, we develop the reputation calculated mechanism to evaluate the reliability of all vehicles in IoV. The proposed framework is feasible for the large heterogeneous vehicular networks and perform the collaborative data analysis in distributed vehicles. The experimental results show that the proposed approach can improve the data sharing efficiency. Furthermore, the reputation mechanism is able to deal with malicious behaviors effectively.
【Keywords】Data sharing; Internet of Vehicles; Reputation mechanism; Federated learning; Blockchain
【标题】RepBFL：基于信誉的基于区块链的联邦学习框架，用于车联网数据共享
【摘要】车联网 (IoV) 实现了智能车辆与互联网的集成以及车辆之间共享数据的协作分析。机器学习技术在 IoV 中的数据分析方面显示出显着的优势和效率。然而，用户数据本质上可能是敏感的，共享这些数据的可靠性和效率难以保证。此外，由于各种分布式车辆的通信间歇性和不可靠，传统的机器学习算法不适用于异构车联网网络。在本文中，我们提出了一种新的信誉机制框架，将 IoV 与区块链和联邦学习相结合，名为 RepBFL。在这个框架中，区块链用于保护车辆之间的共享数据。路边单元 (RSU) 选择信誉良好的车辆节点来共享其数据以进行联邦学习。为了提高数据共享过程的安全性和可靠性，我们开发了信誉计算机制来评估车联网中所有车辆的可靠性。所提出的框架对于大型异构车辆网络是可行的，并在分布式车辆中执行协同数据分析。实验结果表明，该方法可以提高数据共享效率。此外，信誉机制能够有效地处理恶意行为。
【关键词】数据共享；车联网；信誉机制；联邦学习；区块链
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