Efficacy of Machine Learning Algorithms for Enhancing Security and Privacy in Cloud-Based AI Systems

Abstract

The rapid advancement of cloud computing and artificial intelligence (AI) has led to the widespread adoption of cloud-based AI systems across various industries. However, the inherent security and privacy risks associated with these systems pose significant challenges. Machine learning (ML) algorithms have emerged as a promising solution to enhance the security and privacy of cloud-based AI systems. This research article explores the efficacy of ML algorithms in addressing security and privacy concerns, discussing their applications, advantages, limitations, and future research directions. By examining the current state of ML-based security and privacy mechanisms, this article aims to provide valuable insights for researchers, practitioners, and stakeholders in the field of cloud-based AI systems.