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BIG-ABAC:Leveraging Big Data for Adaptive,Scalable,and Context-Aware Access Control
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作者 Sondes Baccouri Takoua Abdellatif 《Computer Modeling in Engineering & Sciences》 2025年第4期1071-1093,共23页
Managing sensitive data in dynamic and high-stakes environments,such as healthcare,requires access control frameworks that offer real-time adaptability,scalability,and regulatory compliance.BIG-ABAC introduces a trans... Managing sensitive data in dynamic and high-stakes environments,such as healthcare,requires access control frameworks that offer real-time adaptability,scalability,and regulatory compliance.BIG-ABAC introduces a transformative approach to Attribute-Based Access Control(ABAC)by integrating real-time policy evaluation and contextual adaptation.Unlike traditional ABAC systems that rely on static policies,BIG-ABAC dynamically updates policies in response to evolving rules and real-time contextual attributes,ensuring precise and efficient access control.Leveraging decision trees evaluated in real-time,BIG-ABAC overcomes the limitations of conventional access control models,enabling seamless adaptation to complex,high-demand scenarios.The framework adheres to the NIST ABAC standard while incorporating modern distributed streaming technologies to enhance scalability and traceability.Its flexible policy enforcement mechanisms facilitate the implementation of regulatory requirements such as HIPAA and GDPR,allowing organizations to align access control policies with compliance needs dynamically.Performance evaluations demonstrate that BIG-ABAC processes 95% of access requests within 50 ms and updates policies dynamically with a latency of 30 ms,significantly outperforming traditional ABAC models.These results establish BIG-ABAC as a benchmark for adaptive,scalable,and context-aware access control,making it an ideal solution for dynamic,high-risk domains such as healthcare,smart cities,and Industrial IoT(IIoT). 展开更多
关键词 ABAC big data CONTEXT-AWARE decision trees adaptive policy SCALABILITY
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