Abstract
At present, the data security and reliability of cloud storage are increasingly threatened by unreliable factors, resulting in major data security problems. As the data security of cloud platforms becomes increasingly prominent, this study starts with the current cybersecurity situation and the challenges of cloud data storage, and emphasizes the urgency of developing an efficient and reliable data verification mechanism. Subsequently, we propose a novel type of machine learning model that leverages advanced algorithms to identify and defend against potential threats of data breaches and corruption. In addition, we have verified the effectiveness of the model through a series of rigorous experiments, and the experimental results show that the model can not only accurately identify various security vulnerabilities, but also adapt to different cloud platform environments, and provide a strong guarantee in terms of data integrity and confidentiality.