Enhancing Security with Machine Learning: Asymmetric Key Encryption and Federated Learning Approach On Review

The exponential growth of data in the digital era presents challenges for ensuring its security.Traditional methods of encryption, though effective, face limitations when combined with distributed computing and privacy-preserving models.This research explores the integration of machine learning, asymmetric key encryption, and federated learning to enhance data security.The paper presents a comprehensive analysis of this approach, detailing its architecture, applications, and potential for widespread adoption in secure data handling.