کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
378971 659244 2011 20 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Using OWL and SWRL to represent and reason with situation-based access control policies
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Using OWL and SWRL to represent and reason with situation-based access control policies
چکیده انگلیسی

Access control is a central problem in confidentiality management, in particular in the healthcare domain, where many stakeholders require access to patients' health records. Situation-Based Access Control (SitBAC) is a conceptual model that allows for modeling healthcare scenarios of data-access requests; thus it can be used to formulate data-access policies, where health organizations can specify their regulations involving access to patients' data according to the context of the request. The model's central concept is the Situation, a formal representation of a patient's data-access scenario.In this paper, we present the SitBAC knowledge framework, a formal healthcare-oriented, context-based access-control framework that makes it possible to represent and implement SitBAC as a knowledge model along with an associated inference method, using OWL and SWRL. Within the SitBAC knowledge framework, scenarios of data access are represented as formal Web Ontology language (OWL)-based Situation classes, formulating data-access rule classes. A set of data-access rule classes makes up the organization's data-access policy. An incoming data-access request, represented as an individual of an OWL-based Situation class, is evaluated by the inference method against the data-access policy to produce an ‘approved/denied’ response. The method uses a Description Logics (DL)-reasoner and a Semantic Web Rule Language (SWRL) engine during the inference process. The DL reasoner is used for knowledge classification and for real-time realization of the incoming data-access request as a member of an existing Situation class to infer the appropriate response. The SWRL engine is used to infer new knowledge regarding the incoming data-access requests, which are required for the realization process.We evaluated the ability of the SitBAC knowledge framework to provide correct responses by representing and reasoning with real-life healthcare scenarios.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Data & Knowledge Engineering - Volume 70, Issue 6, June 2011, Pages 596–615
نویسندگان
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