Role mining based on weights

  • Authors:
  • Xiaopu Ma;Ruixuan Li;Zhengding Lu

  • Affiliations:
  • Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China;Huazhong University of Science and Technology, Wuhan, China

  • Venue:
  • Proceedings of the 15th ACM symposium on Access control models and technologies
  • Year:
  • 2010

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Abstract

Role mining from the existing permissions has been widely applied to aid the process of migrating to an RBAC system. While all permissions are treated evenly in previous approaches, none of the work has employed the weights of permissions in role mining to our knowledge, thus providing the motivation for this work. In this paper, we generalize this to the case where permissions are given weights to reflect their importance to the system. The weights can correspond to the property of operations, the sensitive degree of objects, and the attribute of users associated with permissions. To calculate the weight of permissions, we introduce the concept of similarity between both users and permissions, and use a similarity matrix to reinforce the similarity between permissions. Then we create a link between the reinforced similarity and the weight of permissions. We further propose a weighted role mining algorithm to generate roles based on weights. Experiments on performance study prove the superiority of the new algorithm.