Volume 10,Issue 7
Cloud computing offers numerous benefits, including scalability, cost-effectiveness, and accessibility, making it an attractive solution for various organizations. However, the migration of sensitive data to cloud environments raises significant concerns regarding data privacy protection. This review paper provides a comprehensive overview of data privacy protection technologies in cloud computing. It begins by outlining the historical evolution of cloud computing and associated privacy challenges. The paper then delves into two core themes: access control mechanisms and data encryption techniques. Access control is explored in terms of attribute-based access control (ABAC), role-based access control (RBAC), and break-the-glass mechanisms. Encryption techniques are analyzed by covering homomorphic encryption, differential privacy and federated learning. The paper then offers a comparative analysis of these technologies, highlighting their strengths, weaknesses, and trade-offs in the cloud environment. Finally, the paper addresses the existing challenges and discusses future research directions, including the integration of artificial intelligence for enhanced privacy protection and the development of more robust and efficient encryption methods. This review aims to provide researchers and practitioners with a clear understanding of the current state-of-the-art in data privacy protection technologies for cloud computing and to identify potential avenues for future innovation.