Recent research in dynamic security provisioning in cloud computing focuses on developing adaptive and intelligent mechanisms that can automatically adjust security measures based on real-time threats, workload variations, and user behavior. These studies employ machine learning, reinforcement learning, and zero-trust architectures to dynamically allocate security resources, update policies, and mitigate attacks without human intervention. By integrating automation, context-awareness, and continuous monitoring, dynamic security provisioning enhances system resilience, reduces vulnerabilities, and ensures compliance with evolving security requirements. This approach enables cloud environments to maintain robust protection while efficiently balancing performance and operational overhead.