Volume no :
9 |
Issue no :
1
Article Type :
Scholarly Article
Author :
Arul Selvan M
Published Date :
June, 2025
Publisher :
Journal of Artificial Intelligence and Cyber Security (JAICS)
Page No: 1 - 11
Abstract : Dynamic Access Control Using Context-Aware Algorithms: Implementation Strategies for Identity and Access Managers explores the integration of adaptive, context-sensitive decision-making processes into modern identity and access management (IAM) frameworks to enhance security and operational efficiency. As traditional static access control models become increasingly insufficient in addressing complex, evolving cybersecurity threats and user behaviors, the paper proposes leveraging context-aware algorithms that dynamically adjust access permissions based on real-time contextual information such as user location, device status, time, behavioral patterns, and environmental factors. This approach aims to reduce risks associated with unauthorized access by incorporating situational awareness, thus enabling more granular, risk-based access decisions that adapt to changing conditions without sacrificing usability. The study outlines key implementation strategies for IAM professionals, including the design and deployment of machine learning models and rule-based engines capable of processing heterogeneous context data streams and generating adaptive access policies. It emphasizes the importance of robust data collection mechanisms, secure context validation, and privacy-preserving techniques to ensure the reliability and trustworthiness of contextual inputs. Additionally, the paper discusses architectural considerations, highlighting the integration of context-aware modules into existing IAM infrastructures via modular APIs and middleware to facilitate scalability and interoperability with legacy systems. Practical challenges such as context ambiguity, latency constraints, and potential adversarial manipulations are addressed, alongside proposed mitigation techniques like context fusion, anomaly detection, and continuous policy refinement. The research further explores use cases spanning enterprise environments, cloud services, and Internet of Things (IoT) ecosystems to illustrate the versatility and effectiveness of context-aware dynamic access control in diverse operational scenarios. By advancing a comprehensive framework that combines real-time context analytics with adaptive policy enforcement, the paper contributes to the evolution of IAM paradigms toward more intelligent, proactive, and user-centric security models. Ultimately, this work provides identity and access managers with actionable insights and implementation guidelines for adopting context-aware algorithms, fostering enhanced protection against sophisticated cyber threats while maintaining seamless user experiences in dynamic digital landscapes.
Keyword Dynamic Access Control, Context-Aware Algorithms, Identity and Access Management, Adaptive Security, Real-Time Context Analytics, Risk-Based Access Control
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