Federated Learning Approaches for Privacy-Preserving AI in Cloud
Keywords:
Federated Learning, Privacy-Preserving AI, Cloud Computing, Decentralized Learning, Data Privacy, Secure Aggregation, Differential Privacy.Abstract
As artificial intelligence (AI) continues to advance, concerns over data privacy and security have become paramount. Federated learning emerges as a promising paradigm to address these concerns by enabling collaborative model training across distributed devices while preserving data privacy. This paper explores various federated learning approaches for privacy-preserving AI in cloud environments. We delve into the concepts, methodologies, challenges, and future directions of federated learning, emphasizing its significance in ensuring privacy in AI applications deployed on cloud platforms.
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Published
19-04-2024
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Federated Learning Approaches for Privacy-Preserving AI in Cloud. (2024). Asian American Research Letters Journal, 1(2). https://aarlj.com/index.php/AARLJ/article/view/24