Visual role mining to avoid text complexity using fuzzy logic decision system
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Abstract
Access control is currently one of the most chief topics in information security. The exigent areas of research relating to access control
are to recognize approaches and models to efficiently administer user privileges. With the ever-increasing number of users and IT systems,
organizations have to administer large number of users and permissions in an efficient manner. This paper proposes a new approach for data
visualisation which acts as an aid to Role Engineering .The key idea is to represent the roles within an organisation in a graphical manner so as
to have better elicitation and understanding of the data. This is the primary step to Role Based Access Control (RBAC). The data is viewed in the
form of a Bicluster using a tool named BicOverlapper. Further for best representation of roles we propose a fuzzy decision tree induction
approach to role mining. It facilitates classification of the roles and reduces the problem complexity. The value of this visual analysis in business
environments is demonstrated through examination on real life as well as constructed datasets
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Keywords- Role engineering, Role Based Access Control (RBAC), Bicluster visualisation.
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