This study focuses on network security threats to urban transportation information control systems. With the support of national funds and provincial projects, the system composition and vulnerabilities were analyzed, and different attack modes were explored. We have established a simulation platform based on PYTHON and SUMO, and proposed optimization methods for direct, indirect, and critical intersection signal closure attacks to effectively combat network attacks. However, there are shortcomings in the research, such as not considering the randomness of traffic. In the future, we need to improve our models, build more systematic attack models, and focus on the network security of intelligent connected systems. In summary, this study provides new ideas for the defense of transportation system network security, which is of great significance for future technological development and needs to be continuously optimized to deal with complex threats.