<p>Cybersecurity issues in the cloud computing environment, such as data leakage, malicious attacks, and failed identity authentication, seriously threaten the security of students’ personal information and health data. At present, the student sports health monitoring and management system is confronted with numerous security challenges in the process of data storage, transmission and processing, and there is an urgent need for effective network security protection measures to ensure the stable operation of the system and the security of data. The research adopts a system architecture design that combines C/S and B/S, fully leveraging its advantages of interactivity, speed and security to achieve information sharing. In terms of data analysis, dynamic neural networks and target detection technologies are introduced to enhance the accuracy and efficiency of motion monitoring. Aiming at the security issues of cloud computing networks, key technologies such as multi-factor authentication, data encryption, and access control were studied and applied to the system design, and a secure and reliable network protection system was constructed. Through simulation tests and practical application verification, a comprehensive assessment of the system’s performance and security was conducted. The experimental results show that the system can monitor students’ exercise status in real time and provide personalized health suggestions through intelligent analysis. In terms of cloud computing network security, the multi-factor authentication and data encryption technologies adopted effectively reduce the risk of data leakage, and the access control mechanism ensures the secure storage and access of data. Performance tests of the system under different loads show that both its response time and throughput can meet the actual application requirements, and it can still maintain stable operation under high loads.</p>