Abstract
Cloud computing has become a ubiquitous storage, processing, and data management tool. However, providing strong security measures inside cloud infrastructure remains a primary priority.The purpose of this study is to give an overview of the process of integrating cloud infrastructure with machine learning. The main objective of this work is to leverage machine learning approaches and models for threat identification, anomaly detection, and access control methods in order to protect sensitive data and reduce growing risks in the cloud infrastructure. Ultimately, this research endeavours to enhance the overall security posture of cloud computing, enabling organisations to harness the full potential of the cloud while safeguarding their critical assets and sensitive information.
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