AI-Driven Cloud Security: Enhancing Multi-Tenant Protection with Intelligent Threat Detection

Abstract

As cloud systems become increasingly multi-tenant and dynamic, ensuring robust security remains a paramount concern. This paper explores AI-driven approaches to enhance cloud security by employing advanced threat detection and real-time monitoring mechanisms. The proposed model leverages machine learning algorithms to identify anomalous behaviors, predict potential security breaches, and automate threat mitigation strategies. Experimental evaluations indicate significant improvements in attack detection rates, response times, and overall system resilience. These findings underscore the importance of integrating AI into cloud security frameworks for safeguarding multi-tenant environments.