Policy Evaluation and Dynamic Management Based on Matching Tree for XACML

Hongzhaoning Kang, Gang Liu, Quan Wang, Runnan Zhang, Zichao Zhong, Yu-min Tian
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引用次数: 0

Abstract

As a widely recognized policy language of access control, the eXtensible Access Control Markup Language (XACML) is widely used with its fine-grained and easy-to-read. With the application of XACML, researchers find that the XACML based policy evaluation and policy management methods can no longer meet the current large-scale requests for efficient access and dynamic management requirements. To improve the performance of policy evaluation based on XACML, we propose a policy evaluation method based on the matching tree to search policy efficiently and avoid the extra consumption of invalid policy participation. Furthermore, we propose a policy dynamic management method based on the matching tree to reduce the scale of the policy to be disabled for management, by adding locks in the tree node and the information mapping table. Through theoretical derivation and the factors that may affect its evaluation performance, we verify the improvement of evaluation efficiency. The simulation also shows the improvement of the evaluation engine based on the matching tree compared with OuenAz.
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基于匹配树的XACML策略评估与动态管理
XACML (eXtensible access control Markup language,可扩展访问控制标记语言)是一种被广泛认可的访问控制策略语言,它具有细粒度和易于阅读的特点,被广泛使用。随着XACML的应用,研究人员发现基于XACML的策略评估和策略管理方法已经不能满足当前大规模高效访问和动态管理的要求。为了提高基于XACML的策略评估性能,提出了一种基于匹配树的策略评估方法,有效地搜索策略,避免了无效策略参与的额外消耗。在此基础上,提出了一种基于匹配树的策略动态管理方法,通过在树节点和信息映射表中添加锁,减少了待禁用策略管理的规模。通过理论推导和可能影响其评价绩效的因素,验证了评价效率的提高。仿真结果表明,基于匹配树的评价引擎与OuenAz相比有了很大的改进。
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