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An Incremental Algorithm for the Role Mining Problem
Computers & Security ( IF 5.6 ) Pub Date : 2020-07-01 , DOI: 10.1016/j.cose.2020.101830
Martin Trnecka , Marketa Trneckova

Abstract The role mining process, i.e., computing minimal set of roles from a user-permission assignment relation, is rather incremental task. In a usual situation the set of roles is already established, and the existing permissions are evolved according to current needs. Computation of roles from scratch after each small change in the data is inefficient. Surprisingly, no incremental algorithm for role mining problem exists. The paper proposes a first attempt to an incremental algorithm for role mining problem. The algorithm is tested with several real-world datasets. The results show that the proposed algorithm is significantly faster than non-incremental algorithms, and in many cases, produces a smaller number of roles than the non-incremental version of the algorithm.

中文翻译:

角色挖掘问题的增量算法

摘要 角色挖掘过程,即从用户-权限分配关系中计算最小的角色集,是一种增量任务。通常情况下,角色集已经建立,现有权限根据当前需求进行演进。在数据中的每个小的变化之后从头开始计算角色是低效的。令人惊讶的是,不存在用于角色挖掘问题的增量算法。该论文首次尝试了一种用于角色挖掘问题的增量算法。该算法用几个真实世界的数据集进行了测试。结果表明,所提出的算法明显快于非增量算法,并且在许多情况下,产生的角色数量比非增量版本的算法少。
更新日期:2020-07-01
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