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A Model-driven Approach to Representing and Checking RBAC Contextual Policies
Author(s) -
Ameni Ben Fadhel,
Domenico Bianculli,
Lionel Briand,
Benjamin Hourte
Publication year - 2016
Publication title -
open repository and bibliography (university of luxembourg)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2857705.2857709
Subject(s) - role based access control , computer science , access control , context (archaeology) , computer security , paleontology , biology
Among the various types of Role-based access control (RBAC) policies proposed in the literature, contextual policies take into account the user's location and the time at which she requests an access. The precise characterization of the context in such policies and the definition of an access decision procedure for them are non-trivial ntasks, since they have to take into account the various facets of the temporal and spatial expressions occurring in these policies. Existing approaches for modeling contextual policies do not support all the various spatio-temporal concepts and often do not provide an access decision procedure. In this paper, we propose a model-driven approach to representing and checking RBAC contextual policies. We introduce GemRBAC+CTX, an extension of a generalized conceptual model for RBAC, which contains all the concepts required to model contextual policies. We formalize these policies as constraints, using the Object Constraint Language (OCL), on the GemRBAC+CTX model, as a way to operationalize the access decision for user's requests using model-driven technologies. We show the application of GemRBAC+CTX to model the RBAC contextual policies of an application developed by HITEC Luxembourg, a provider of situational-aware information management systems for emergency scenarios. The use of GemRBAC+CTX has allowed the engineers of HITEC to define several new types of contextual policies, with a fine-grained, precise description of contexts. The preliminary experimental results show the feasibility of applying our model-driven approach for making access decisions in real systems.

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