Graduate Seminar (2009 Fall)
Title:
Statistics & Clustering Based Framework for Efficient XACML Policy Evaluation

Said M. Marouf
Ph.D student
Department of Software & Information Systems
University of North Carolina at Charlotte
September 4 at 3:00pm
106 Woodward
Abstract:
The adoption of XACML as the standard for specifying access control
policies for various applications, especially web services is vastly
increasing. A policy evaluation engine can easily become a bottleneck
when enforcing large policies. In this paper we propose an adaptive
approach for XACML policy optimization. We proposed a clustering
technique that categorizes policies and rules within a policy set and
policy respectively in respect to target subjects. Furthermore, we
propose a usage based framework that computes access request
statistics to dynamically optimize the ordering of policies within a
policy set and rules within a policy. Reordering is applied to
categorized policies and rules from our proposed clustering technique.
To evaluate the performance of our framework, we conducted extensive
experiments on XACML policies. We evaluated separately the improvement
due to categorization and to reordering techniques, in order to assess
the policy sets targeted by our techniques. The experimental results
show that our approach is orders of magnitude more efficient than the
standard Sun PDP.
Bio:
I'm a second year PhD student in the department of Software &
Information Systems here at UNC-Charlotte. I received my Bachelor's
degree in Computer Engineering from the Islamic University in Gaza.
After my graduation, I received the Fulbright scholarship to study my
Master's degree in Software Engineering at the University of Wisconsin-
La Crosse. My research focus then was on the security vulnerabilities
within the Java programming language.
My current research is in the area of Access Control, including the
performance optimization of XACML PDP Engines. I've also worked on
implementing dynamic & adaptable XACML PDP engines. My newest research
focus is on building an access control policy recommendation system.
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