A new role mining framework to elicit business roles and to mitigate enterprise risk

被引:17
作者
Colantonio, Alessandro [1 ,2 ]
Di Pietro, Roberto [2 ]
Ocello, Alberto [1 ]
Verde, Nino Vincenzo [2 ]
机构
[1] Engiweb Secur, Rome, Italy
[2] Univ Roma Tre, Dipartimento Matemat, Rome, Italy
关键词
RBAC; Role engineering; Role mining; Risk management; Clustering coefficient;
D O I
10.1016/j.dss.2010.08.022
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Role-based access control (RBAC) allows to effectively manage the risk derived from granting access to resources, provided that designed roles are business-driven. Role mining represents an essential tool for role engineers, but existing techniques are not able to elicit roles with an associated clear business meaning. Hence, it is difficult to mitigate risk, to simplify business governance, and to ensure compliance throughout the enterprise. To elicit meaningful roles, we propose a methodology where data to analyze are decomposed into smaller subsets according to the provided business information. We introduce two indices. minability and similarity, that drive the decomposition process by providing the expected complexity to find roles with business meaning. The proposed methodology is rooted on a sound theoretical framework. Moreover. experiments on real enterprise data support its effectiveness. (C) 2010 Elsevier B.V. All rights reserved.
引用
收藏
页码:715 / 731
页数:17
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