Adaptive Role-Based Access Control for Dynamic Applications

Abstract

Role-Based Access Control (RBAC) has long served as a cornerstone of enterprise access management due to its simplicity and structured approach. However, traditional RBAC models often lack the responsiveness needed to address dynamic threats and contextual risks in modern computing environments. This paper introduces an Adaptive RBAC framework that integrates behavioral context, real-time threat intelligence, and dynamic policy enforcement to strengthen access control. We design and implement an enhanced RBAC system capable of detecting anomalous access behavior, adjusting user roles in real time, and providing responsive mitigations. Comparative evaluation demonstrates significant improvements in threat detection, role accuracy, and response measures across diverse user groups, albeit with modest increases in processing overhead. The proposed model strikes a balance between security and usability, making it a compelling upgrade for enterprises requiring context-aware security postures. This work contributes to bridging the gap between static access models and the evolving needs of secure, adaptive systems.