Research on Cloud Computing Network Security Framework Based on Machine Learning

This paper studies and proposes a machine learning-based network security framework for cloud computing, which aims to deal with diverse security threats in cloud environments. By designing data collection, feature extraction, model training and dynamic protection mechanisms, the framework can detect and respond to intrusions, malware and abnormal behaviors in the cloud platform in real time. The results show that machine learning has significant advantages in improving detection accuracy and response speed, and the framework has adaptive learning ability and can dynamically adjust protection strategies.