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Mining roles with semantic meanings
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Symposium on Access Control Models and Technologies archive
Proceedings of the 13th ACM symposium on Access control models and technologies table of contents
Estes Park, CO, USA
SESSION: Role mining table of contents
Pages 21-30  
Year of Publication: 2008
ISBN:978-1-60558-129-3
Authors
Ian Molloy  Purdue University, West Lafayette, IN
Hong Chen  Purdue University, West Lafayette, IN
Tiancheng Li  Purdue University, West Lafayette, IN
Qihua Wang  Purdue University, West Lafayette, IN
Ninghui Li  Purdue University, West Lafayette, IN
Elisa Bertino  Purdue University, West Lafayette, IN
Seraphin Calo  IBM T.J. Watson Research Center, Hawthorne, NY
Jorge Lobo  IBM T.J. Watson Research Center, Hawthorne, NY
Sponsors
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

With the growing adoption of role-based access control (RBAC) in commercial security and identity management products, how to facilitate the process of migrating a non-RBAC system to an RBAC system has become a problem with significant business impact. Researchers have proposed to use data mining techniques to discover roles to complement the costly top-down approaches for RBAC system construction. A key problem that has not been adequately addressed by existing role mining approaches is how to discover roles with semantic meanings. In this paper, we study the problem in two settings with different information availability. When the only information is user-permission relation, we propose to discover roles whose semantic meaning is based on formal concept lattices. We argue that the theory of formal concept analysis provides a solid theoretical foundation for mining roles from userpermission relation. When user-attribute information is also available, we propose to create roles that can be explained by expressions of user-attributes. Since an expression of attributes describes a real-world concept, the corresponding role represents a real-world concept as well. Furthermore, the algorithms we proposed balance the semantic guarantee of roles with system complexity. Our experimental results demonstrate the effectiveness of our approaches.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Boost C++ Libraries. http://www.boost.org/.
 
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M. P. Gallaher, A. C. O'Connor, and B. Kropp. The economic impact of role-based access control. Planning Report 02-1, National Institute of Standards and Technology, Mar. 2002.
 
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C. Lindig. Fast concept analysis. In G. Stumme, editor, Working with Conceptual Structures - Contributions to ICCS 2000, 2000.
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S. D. Stoller, P. Yang, C. R. Ramakrishnan, and M. I. Gofman. Efficient policy analysis for administrative role based access control, Oct. 2007.
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Collaborative Colleagues:
Ian Molloy: colleagues
Hong Chen: colleagues
Tiancheng Li: colleagues
Qihua Wang: colleagues
Ninghui Li: colleagues
Elisa Bertino: colleagues
Seraphin Calo: colleagues
Jorge Lobo: colleagues