区块链辅助的VANET中车辆声誉管理方法

Blockchain-assisted vehicle reputation management method for VANET

车载自组网是一种以车辆为节点的特殊的移动自组织网络,其节点存在高度移动性。车辆间通过网络交互实现海量的数据共享,以此来提高智能交通系统的运输效率和安全性。然而恶意车辆的存在给车载自组网乃至整个交通运输系统带来了严重的安全隐患。针对该问题,提出一种改进的三值主观逻辑算法来评估车辆的声誉值,利用声誉阈值识别恶意车辆,利用信任路线搜索算法提高计算准确率。该方法使用区块链技术分布式存储信任数据库,同时保障了数据的不可篡改性。声誉评估算法联合车辆节点的历史周期声誉值、历史交互信息以及交互频率等因素周期化更新车辆声誉值。此外,通过结合深度优先搜索算法更精准地确定车辆间的信任路径,利用六度空间分离理论来解决信任路径过长导致的信息量较低问题,设置声誉阈值过滤信息量较低的信任路径,进一步提高了计算精确度。实验结果表明,相较于传统算法,该算法对于恶意车辆的识别效率有显著提高,在面对群组串通攻击和On-off等攻击时表现出良好的抗攻击性能。

The Vehicular Ad-hoc NETworks(VANET)is a special Mobile Ad-hoc NETworks(MANET)with vehicles as nodes which have high mobility.The vehicles interact with each other through the network to achieve massive data sharing,so as to improve the transportation efficiency and safety of the Intelligent Transportation System(ITS).However,the existence of malicious vehicles brings serious security risks to the VANET and even to the entire transportation system.To address this problem,an improved Three Valued Subjective Logic(3 VSL)algorithm is proposed to evaluate the reputation value of vehicles and identify malicious vehicles using reputation thresholds,and the trusted route search algorithm is used to improve the calculation accuracy.The method uses blockchain technology to store the trust database in a distributed manner,and at the same time guarantees the immutability of the data.It periodically updates the vehicle reputation value by combining the historical periodic reputation value of vehicle nodes,historical interaction information,and interaction frequency.In addition,the depth-first search(DFS)algorithm is used to determine the trust path between vehicles more precisely,and the six-degree spatial separation theory is used to solve the problem of low information due to the long trust path,and reputation thresholds are set to filter trust paths with a low information volume,which further improves the computational accuracy.Simulation results show that,compared with the traditional algorithms,the proposed algorithm has a significant improvement in the identification efficiency of malicious vehicles,and shows a good anti-attack performance in the face of group collusion attacks and On-off attacks.