Research on Network Security Intrusion Detection System Based on Deep Learning

With the increasing complexity of network attacks, traditional intrusion detection methods have been difficult to meet the security requirements. Intrusion detection system based on deep learning greatly enhances the defense capability of network information security through automatic learning and adaptive adjustment. This paper describes the application of deep learning technology in the field of network security, focusing on the remarkable efficiency of identifying malware, analyzing network data traffic, detecting abnormal behavior and resisting spoofing attacks. An intrusion detection system based on deep learning is proposed, which includes system architecture, module design, model integration and real-time response mechanism. The system can realize efficient and accurate detection and real-time response.