Privacy -aware role based access control

Qun Ni, Purdue University


Current proposals for access control languages cannot specify policies required by specific application scenarios (e.g. a database system to enforce privacy regulations), may also contain design flaws, and are incompatible. In this dissertation, we extend RBAC with new components to meet requirements from privacy-aware access control which is required to enforce privacy laws and regulations in organizational computing environments. We propose an access control language for provenance access control which requires aggregating access decisions from different sources and controlling the access to different sections of provenance information. We investigate various problems in risk-based access control. Risk-based access control is particularly useful for making access decisions in an emergency. Subjects without sufficient privilege in an emergency have to be given authorization to access sensitive information in different ways, based on their risk estimations. We also identify design flaws in representative proposals, e.g. XACML, and present corresponding solutions. We finally propose an extensible functional access control language that combines the benefits of XACML and RBAC without their drawbacks. The language is attribute-based and context-centric and supports sophisticated error handling and flexible decision aggregation methods. We also show the language is able to meet requirements from all specific application domains discussed in this dissertation.




Bertino, Purdue University.

Subject Area

Computer science

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