Towards knowledge level privacy and security using RDF/RDFS and RBAC

Information privacy and security plays a major role in domains where sensitive information is handled, such as case studies of rare diseases. Currently, security for accessing any sensitive information is provided by various mechanisms at the user/system level by employing access control models such as Role Based Access Control. However, these approaches leave security at the knowledge level unattended, which can be inadequate. For example, in healthcare, ontology-based information extraction is employed for extracting medical knowledge from sensitive structured/unstructured data sources. These information extraction systems act on sensitive data sources which are protected against unauthorized access at the system level based on the user, context and permissions, but the knowledge that can be extracted from these sources is not. In this paper we tackle the security or access control at the knowledge level by presenting a model, to enforce knowledge security/access by leveraging knowledge sources (currently focused on RDF) with the RBAC model. The developed model filters out knowledge by means of binary permissions on the knowledge source, providing each user with a different view of the knowledge source.