Evaluating role mining algorithms
Ian Molloy, Ninghui Li, et al.
SACMAT 2009
Many access control policy languages, e.g., XACML, allow a policy to contain multiple sub-policies, and the result of the policy on a request is determined by combining the results of the sub-policies according to some policy combining algorithms (PCAs). Existing access control policy languages, however, do not provide a formal language for specifying PCAs. As a result, it is difficult to extend them with new PCAs. While several formal policy combining algebras have been proposed, they did not address important practical issues such as policy evaluation errors and obligations; furthermore, they cannot express PCAs that consider all sub-policies as a whole (e.g., weak majority or strong majority). We propose a policy combining language PCL, which can succinctly and precisely express a variety of PCAs. PCL represents an advancement both in terms of theory and practice. It is based on automata theory and linear constraints, and is more expressive than existing approaches. We have implemented PCL and integrated it with SUN's XACML implementation. With PCL, a policy evaluation engine only needs to understand PCL to evaluate any PCA specified in it. Copyright 2009 ACM.
Ian Molloy, Ninghui Li, et al.
SACMAT 2009
Ian Molloy, Hong Chen, et al.
ACM TISSEC
John Karat, Clare-Marie Karat, et al.
IBM J. Res. Dev
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Int. J. Inf. Secur.