Exploring the automated development of AI-based computer network security programs

With the rapid development of the information society, computer network security has become a key area of national security. Artificial Intelligence (AI) technology has been increasingly used in network security defense, significantly improving the accuracy and efficiency of threat detection. This study explores the automated development of AI-based computer network security programs, aiming to build an intelligent and adaptive network security defense system. By integrating machine learning and deep learning techniques, the system is able to monitor network activities in real time and automatically identify and respond to various network attacks and abnormal behaviors. The research covers key modules such as data acquisition and preprocessing, intelligent analysis and decision-making, and automated response and repair strategies, and implements the functions of these modules using the Python programming language. The system test results show that the defense system performs well in handling large-scale network traffic and identifying multiple network attacks and abnormal behaviors with high throughput, fast response and low resource utilization. The system formulates corresponding defense strategies for different attack types, which effectively protects the security of the network system. This study provides an innovative solution in the field of network security and demonstrates the great potential of AI technology in network security defense.