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Role Mining Using Boolean Matrix Decomposition With Hierarchy

机译:使用Boolean矩阵分解与层次结构的角色挖掘

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摘要

With the increasing adoption of role-based access control (RBAC) in business security, how to apply role mining technology to aid the process of migrating a non-RBAC system to a RBAC system has become an important problem. Numerous approaches have been proposed to use data mining techniques to discover the roles. However, the Boolean matrix decomposition is still little used in role mining, because Boolean matrix decomposition without hierarchy can not express the hierarchical relationships of the RBAC model. In this paper, we propose a new method of Boolean matrix decomposition which can clearly express the hierarchical relationships of the RBAC model. Then, we introduce the cost-utility analysis method in economics to guide the role mining. Our optimization goal is not only to minimize the administration costs, but also to maximize the utility of RBAC configuration in the meanwhile. We further propose a heuristic algorithm to find the optimal solution with the Boolean matrix decomposition. The experimental results demonstrate the effectiveness of our approach.
机译:随着在业务安全中的基于角色的访问控制(RBAC)的增加,如何应用角色挖掘技术来帮助将非RBAC系统迁移到RBAC系统的过程已成为一个重要问题。已经提出了许多方法来使用数据挖掘技术来发现角色。但是,Boolean矩阵分解仍然很少用于角色挖掘,因为没有层次结构的布尔矩阵分解不能表达RBAC模型的层次关系。在本文中,我们提出了一种新的布尔矩阵分解方法,其可以清楚地表达RBAC模型的层次关系。然后,我们在经济学中介绍了成本实用性分析方法,以指导角色挖掘。我们的优化目标不仅可以最大限度地减少管理成本,而且还可以在同时最大化RBAC配置的效用。我们进一步提出了一种启发式算法,可以使用布尔矩阵分解找到最佳解决方案。实验结果表明了我们方法的有效性。

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