<p>Cloud computing is a leading technology in Information Technology, prompted by virtualization that allows optimal resource utilization and faultless delivery of services. However current cloud frameworks are hampered by issues such as security loopholes, task scheduling inefficiencies, and convergence challenges that affect performance. To overcome these limitations, this research proposes Enhanced Advanced Encryption Standard (EAES) and Adaptive Elephant Herding Optimization (AEHO) to improve security and dynamic task scheduling optimization. The proposed system model includes cloud users, tasks, virtual machines (VMs), and computing resources. Virtualization is employed for efficient VM migration to ensure optimum resource allocation and service availability. AEHO ensures the optimal choice of VM through available resource limits, power consumption, and computing efficiency. This provides better throughput, lower operation costs, and lesser energy consumption. EAES provides an improved security boost for the cloud by detecting hypervisor attacks and defusing potential cyberattacks for improved data protection. A comparative study confirms that the new approach performs better than other existing approaches in terms of improved reliability, reduced computational complexity, improved security, and improved system performance. Such results confirm the effectiveness of EAES and AEHO in enhancing cloud computing performance with cost-effective and secure operation.</p>