Model construction of network security protection based on abnormal network behaviors Detection

In order to explore how to use artificial intelligence algorithm technology to improve network security protection ability, this study combines machine learning, deep learning and other algorithms to realize automatic identification and response to potential network attack behavior, and on this basis, designs a network intrusion detection system based on artificial intelligence algorithm. The system first preprocesses the collected network traffic data, extracts key features, and then classifies features through machine learning models to identify abnormal network behaviors, and further uses deep learning algorithms to model complex attack patterns, improving the accuracy and robustness of detection. The experimental results show that the system can improve the efficiency and intelligence level of network security protection, and provide strong support for building a more secure network environment.