Machine Learning-Based Encryption Techniques for Secure File Storage on Servers

In the era of digital transformation, securing data has become a paramount concern for organizations and individuals alike. Traditional encryption techniques, while robust, face challenges in adapting to increasingly sophisticated cyber threats. This paper explores the integration of machine learning (ML) with encryption methodologies to enhance the security of file storage on servers. By leveraging ML algorithms, the proposed approach aims to dynamically adapt encryption mechanisms based on real-time threat analysis, providing a resilient and adaptive security framework.