A fine-grained context-aware access control model for health care and life science linked data

Abstract

Health Care and Life Sciences (HCLS) have long been a test-bed for the standards proposed by the W3C to build the Semantic Web. One of the challenges to HCLS Linked Data is access control. In this paper, we present a fine-grained context-aware access model for HCLS Linked Data based on Semantic Web tools. The model consists of two basic components: ontology base and access policy. Ontology base refers to a set of ontologies that include subject ontology, resource ontology, environment ontology, and action ontology. In the access policy module, we describe the access policy with eXtensible Access Control Markup Language (XACML) model, which allows users to achieve access rule reproduction by defining the semantic scope and inference rules among different entities. Results of the analysis indicate that indicates that our model expands the scopes of authorization rules for users. Inference of semantic authorization rules is also realized. These rules enable fine-grained access to data and meet the need for dynamic change of HCLS Linked Data. Finally, we show the process of authorization and present a system framework. Simulation experiments verify the acceptability of our model in protecting secured data.