AI/ML FOR DATA PRIVACY AND ENCRYPTION IN CLOUD COMPUTING
Keywords:
Cloud Computing Security, AI/ML-Enhanced Encryption, Privacy-Preserving Algorithms, Homomorphic Encryption, Federated LearningAbstract
As cloud computing becomes increasingly pervasive, ensuring data privacy and security remains a critical concern. Artificial intelligence (AI) and machine learning (ML) offer promising solutions for enhancing data privacy and developing advanced encryption techniques in cloud environments. This review article explores how AI and ML are applied to improve data privacy, including the development of intelligent encryption methods, privacy-preserving algorithms, and automated data protection mechanisms. We examine various approaches, such as homomorphic encryption, secure multi-party computation, and differential privacy, and assess their integration with AI/ML technologies. The article provides an overview of current research, evaluates the effectiveness of different techniques, and discusses the trade-offs involved. It concludes with a discussion on future trends and potential areas for further research in leveraging AI/ML for data privacy and encryption in cloud computing.
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