Modeling and inferring on Role-Based Access Control policies using data dependencies

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Abstract

Role-Based Access Control (RBAC) models are becoming a de facto standard, greatly simplifying management and administration tasks. Organizational constraints were introduced (e.g.: mutually exclusive roles, cardinality, prerequisite roles) to reflect peculiarities of organizations. Thus, the number of rules is increasing and policies are becoming more and more complex: understanding and analyzing large policies in which several security officers are involved can be a tough job. There is a serious need for administration tools allowing analysis and inference on access control policies. Such tools should help security officers to avoid defining conflicting constraints and inconsistent policies. This paper shows that theoretical tools from relational databases are suitable for expressing and inferring on RBAC policies and their related constraints. We focused on using Constrained Tuple-Generating Dependencies (CTGDs), a class of dependencies which includes traditional other ones. We show that their great expressive power is suitable for all practical relevant aspects of RBAC. Moreover, proof procedures have been developed for CTGDs: they permit to reason on policies. For example, to check their consistency, to verify a new rule is not already implied or to check satisfaction of security properties. A prototype of RBAC policies management tool has been implemented, using CTGDs dedicated proof procedures as the underlying inference engine. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Thion, R., & Coulondre, S. (2006). Modeling and inferring on Role-Based Access Control policies using data dependencies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4080 LNCS, pp. 914–923). Springer Verlag. https://doi.org/10.1007/11827405_89

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