AI-Driven Cloud User Validation for Secure Resource Allocation - Karthik Kambhampati (International Journal of Intelligent Systems and Applications in Engineering, 2022)
Cloud computing offers scalable, elastic, and on-demand services but faces major challenges in ensuring user authentication, secure access, and optimal resource distribution. Service Level Agreement (SLA) violations and malicious intrusions represent persistent threats that degrade reliability and trust in cloud ecosystems. Traditional validation methods often struggle to adapt to dynamic workloads and evolving attack vectors. In this paper, we present an AI-driven validation and resource allocation framework that integrates neural classification for authentication, machine-learning-based SLA prediction, and reinforcement learning (RL)-driven resource provisioning. The system demonstrates improved detection accuracy of unauthorized users and reduced SLA violations under variable workloads. Expanded simulations highlight that incorporating AI improves not only security but also fairness, energy efficiency, and cost optimization. This paper contributes a holistic methodology that addresses the dual challenges of security and performance in multi-tenant cloud infrastructures.