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Computer Science > Computers and Society

arXiv:2403.08264 (cs)
[Submitted on 13 Mar 2024]

Title:GPT, Ontology, and CAABAC: A Tripartite Personalized Access Control Model Anchored by Compliance, Context and Attribute

Authors:Raza Nowrozy, Khandakar Ahmed, Hua Wang
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Abstract:As digital healthcare evolves, the security of electronic health records (EHR) becomes increasingly crucial. This study presents the GPT-Onto-CAABAC framework, integrating Generative Pretrained Transformer (GPT), medical-legal ontologies and Context-Aware Attribute-Based Access Control (CAABAC) to enhance EHR access security. Unlike traditional models, GPT-Onto-CAABAC dynamically interprets policies and adapts to changing healthcare and legal environments, offering customized access control solutions. Through empirical evaluation, this framework is shown to be effective in improving EHR security by accurately aligning access decisions with complex regulatory and situational requirements. The findings suggest its broader applicability in sectors where access control must meet stringent compliance and adaptability standards.
Subjects: Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR)
Cite as: arXiv:2403.08264 [cs.CY]
  (or arXiv:2403.08264v1 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2403.08264

Submission history

From: Raza Nowrozy [view email]
[v1] Wed, 13 Mar 2024 05:30:30 UTC (433 KB)
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