Sensors, communication devices, and complex software systems have been integrated into vehicles, which not only improves driving experience and security, but also greatly increases the network security threats faced by vehicles. This study proposed an intelligent networked vehicle information security detection system based on artificial intelligence. The system used Convolutional Neural Network (CNN) for real-time monitoring and analysis of vehicle communication data. In addition, the system also integrated data leakage protection mechanisms to ensure the security of sensitive information during transmission. In this study, a simulated intelligent connected vehicle environment was constructed, and a large amount of normal and abnormal data was collected for training and validating the model of this study. The experimental results showed that the detection accuracy of the CNN based detection system reached up to 97%, with superior robustness and false alarm rates below 5%. The system maintained high detection accuracy while keeping the false alarm rate within an acceptable range.