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Evaluating role mining algorithms

Published: 03 June 2009 Publication History

Abstract

While many role mining algorithms have been proposed in recent years, there lacks a comprehensive study to compare these algorithms. These role mining algorithms have been evaluated when they were proposed, but the evaluations were using different datasets and evaluation criteria. In this paper, we introduce a comprehensive framework for evaluating role mining algorithms. We categorize role mining algorithms into two classes based on their outputs; Class 1 algorithms output a sequence of prioritized roles while Class 2 algorithms output complete RBAC states. We then develop techniques that enable us to compare these algorithms directly. We also introduce a new role mining algorithm and two new ways for algorithmically generating datasets for evaluation. Using synthetic as well as real datasets, we compared nine role mining algorithms. Our results illustrate the strengths and weaknesses of these algorithms.

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cover image ACM Conferences
SACMAT '09: Proceedings of the 14th ACM symposium on Access control models and technologies
June 2009
258 pages
ISBN:9781605585376
DOI:10.1145/1542207
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Publication History

Published: 03 June 2009

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Author Tags

  1. evaluation
  2. rbac
  3. role engineering
  4. role mining

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SACMAT '09 Paper Acceptance Rate 24 of 75 submissions, 32%;
Overall Acceptance Rate 177 of 597 submissions, 30%

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