作为移动互联网的一部分,车联网在近年来获得了长足发展。车载电子支付是车联网下一步的发展方向之一,涉及到用户的财产安全等。因此,如何有效防范车联网车载电子支付中可能出现的风险成为研究的一个热点。介于车联网电子支付中缺乏历史数据资料和现场难收集的特点,本文分析了车联网电子支付中的风险因素,运用贝叶斯网络方法,结合专家的意见,建立了一种贝叶斯网络预测模型进行风险预测。研究发现,本文所提出的预测模型,综合考虑了车联网电子支付中软件系统安全性、资金损失程度、风险发生频度等支付的关键风险因素,能较好完成车联网电子支付中的风险评估与预测,便于风险管理。 As part of the mobile Internet, car networking has made great strides in recent years. Car electronic payment is the next step in the development direction of the car network, involving the user’s property safety. Therefore, how to effectively prevent the risks that may appear in the vehicle-mounted electronic payment of car network has become a hot spot in the research. Due to the lack of historical data and hard-to-collect data in the networked electronic payment, this paper analyzes the risk factors in the vehicle networked electronic payment, uses the Bayesian network method and the expert opinion to establish a Bayesian network Forecasting model for risk prediction. The study finds that the forecasting model proposed in this paper considers the key risk factors such as the security of software system, the degree of financial loss and the frequency of occurrence of risks in the electronic payment of vehicle network, and can well complete the risk assessment in the networked electronic payment And forecast, easy to risk management.