With the development of the intelligent automobile industry, its network security issues have become increasingly prominent. According to statistics, there are over 3700 core vulnerabilities related to vehicle control, in vehicle communication, and data storage in intelligent connected vehicles. Between 2023 and September 2024, there were more than 20 data breaches related to car companies in China, exposing severe challenges in the industrys security protection. In this context, threat modeling technology has become a key tool for network security protection due to its ability to systematically analyze and evaluate potential risks. At present, classic modeling methods such as STRIDE model and attack tree have shown certain advantages in risk identification and analysis, but their adaptability to specific scenarios of intelligent vehicles is limited, making it difficult to cover complex scenarios of vehicle networking interaction and data flow, and lacking organic connection with subsequent protection design. Therefore, the paper explores the design of intelligent vehicle network security risk protection based on threat modeling, in order to improve the level of intelligent vehicle network security risk protection.