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Symbolic reachability analysis for parameterized administrative role based access control
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Symposium on Access Control Models and Technologies archive
Proceedings of the 14th ACM symposium on Access control models and technologies table of contents
Stresa, Italy
SESSION: XACML and RBAC table of contents
Pages 165-174  
Year of Publication: 2009
ISBN:978-1-60558-537-6
Authors
Scott D. Stoller  Stony Brook University, Stony Brook, NY, USA
Ping Yang  Binghamton University, Binghamton, NY, USA
Mikhail Gofman  Binghamton University, Binghamton, NY, USA
C. R. Ramakrishnan  Stony Brook University, Stony Brook, NY, USA
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

Role based access control (RBAC) is a widely used access control paradigm. In large organizations, the RBAC policy is managed by multiple administrators. An administrative role based access control (ARBAC) policy specifies how each administrator may change the RBAC policy. It is often difficult to fully understand the effect of an ARBAC policy by simple inspection, because sequences of changes by different administrators may interact in unexpected ways. ARBAC policy analysis algorithms can help by answering questions, such as user-role reachability, which asks whether a given user can be assigned to given roles by given administrators. Allowing roles and permissions to have parameters significantly enhances the scalability, flexibility, and expressiveness of ARBAC policies. This paper defines PARBAC, which extends the classic ARBAC97 model to support parameters, and presents an analysis algorithm for PARBAC. To the best of our knowledge, this is the first analysis algorithm specifically for parameterized ARBAC policies. We evaluate its efficiency by analyzing its parameterized complexity and benchmarking it on case studies and synthetic policies.


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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Collaborative Colleagues:
Scott D. Stoller: colleagues
Ping Yang: colleagues
Mikhail Gofman: colleagues
C. R. Ramakrishnan: colleagues