Research on intelligent defense system of attack detection and response in computer network supply chain

By infiltrating or tampering with supply chain links, supply chain attacks have the characteristics of strong concealment and wide influence, and traditional defense methods are difficult to deal with effectively. The intelligent defense system designed in this study integrates AI, machine learning and big data analysis, and builds a solid network security defense line through real-time monitoring, intelligent analysis, rapid response and continuous improvement. The architecture includes intelligent detection module, rapid response module, security audit module, central control module and data storage and analysis module. The detection method combines static detection and dynamic detection, and realizes the accurate identification of supply chain attacks through techniques such as symbol execution, abstract syntax tree (AST) analysis and system call sequence modeling. Based on quantitative threat assessment model and dynamic response priority calculation, rapid response mechanism can quickly isolate infected systems, fix vulnerabilities and restore services. The experimental results show that the intelligent defense system is significantly superior to the traditional methods in the core indicators such as detection accuracy, response speed and recovery success rate. The false alarm rate is reduced by more than 50%, the initial response and complete containment time are shortened by about 55% respectively, and the error of threat assessment model is controlled within 5%, which effectively solves the hidden and interlocking problems of supply chain attacks and provides a strong guarantee for computer network security.