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Meeting Cardinality Constraints in Role Mining

机译:在角色挖掘中满足基数约束

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Role mining is a critical step for organizations that migrate from traditional access control mechanisms to role based access control (RBAC). Additional constraints may be imposed while generating roles from a given user-permission assignment relation. In this paper we consider two such constraints which are the dual of each other. A role-usage cardinality constraint limits the maximum number of roles any user can have. Its dual, the permission-distribution cardinality constraint, limits the maximum number of roles to which a permission can belong. These two constraints impose mutually contradictory requirements on user to role and role to permission assignments. An attempt to satisfy one of the constraints may result in a violation of the other. We show that the constrained role mining problem is NP-Complete and present heuristic solutions. Two distinct frameworks are presented in this paper. In the first approach, roles are initially mined without taking the constraints into account. The user-role and role-permission assignments are then checked for constraint violation in a post-processing step, and appropriately re-assigned, if necessary. In the second approach, constraints are enforced during the process of role mining. The methods are first applied on problems that consider the two constraints individually, and then with both considered together. Both methods are evaluated over a number of real-world data sets.
机译:对于从传统访问控制机制迁移到基于角色的访问控制(RBAC)的组织而言,角色挖掘是至关重要的一步。从给定的用户权限分配关系生成角色时,可能会施加其他约束。在本文中,我们考虑两个这样的约束条件,它们是彼此对偶的。角色使用基数约束限制了任何用户可以拥有的最大角色数。它的双重权限分配基数约束限制了权限可以属于的最大角色数。这两个约束对用户到角色和角色到权限分配提出了相互矛盾的要求。尝试满足其中一个约束可能会导致违反另一个约束。我们证明了约束角色挖掘问题是NP-Complete并提出了启发式解决方案。本文提出了两个不同的框架。在第一种方法中,最初是在不考虑约束的情况下挖掘角色的。然后,在后处理步骤中检查用户角色和角色权限分配是否违反约束,并在必要时进行适当的重新分配。在第二种方法中,在角色挖掘过程中强制执行约束。这些方法首先应用于分别考虑两个约束的问题,然后将两个约束一起考虑。两种方法均通过大量实际数据集进行评估。

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