Research on Cloud Platform Computing Security and Integrity Protection System Based on Machine Learning

Cloud computing has gained widespread popularity in various fields due to its benefits, including on-demand resource provisioning, scalability, and cost-effectiveness. However, the rapid expansion of cloud computing services has raised significant concerns about the security and integrity of cloud data. This paper proposes a security and integrity protection system for cloud computing based on machine learning algorithms. The proposed system employs various machine learning algorithms, including Random Forest, Support Vector Machine, and Naive Bayes, to detect and prevent security threats in cloud computing. Additionally, the proposed system employs encryption techniques to ensure data confidentiality in the cloud. Experimental results demonstrate that the proposed system can effectively detect and prevent security threats, thus preserving the integrity of cloud data.