Authors : Bhushan Chaudhari , Dr. Nilesh Yuvaraj Choudhary
DOI : 10.46335/IJIES.2025.10.9.9
Abstract – 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.
