Simulation Design of Security Situation Awareness Model of Vehicle Networking Based on RBF Neural Network

In recent years, the rapid growth of the Internet of Vehicles (IOV) has made it more and more convenient for people to travel. However, the IOV brings convenience to people and also faces a lot of network security problems. Frequent network security incidents of car networking have caused huge economic losses to enterprises and governments. However, the traditional network security defense devices of the IOV are all single-point security defense technologies, which lack effective cooperation with each other and cannot control the network security situation of the IOV as a whole. In order to establish a multi-level and three-dimensional network security defense system of the IOV, the network security situation assessment technology uses a specific comprehensive analysis method and a reliable situation assessment model to assess the overall network situation by integrating multiple data sources, thus reflecting the current network security situation. In this paper, a hierarchical network security situation assessment model of vehicle networking based on RBFNN is proposed according to the characteristics of vehicle networking. Through experiments, the proposed algorithm is compared with the existing prediction methods, which verifies the feasibility of the proposed algorithm in network security situation awareness (NSSA) and the accuracy of the prediction results.