XACML Policy Evaluation Engine Based on Multi-Level Optimization Technology
基于多层次优化技术的XACML 策略评估引擎

This paper proposes an implementation scheme of XACML (extensible access control markup language) policy evaluation engine based on multi-level optimization technology, MLOBEE (multi-level optimization based evaluation engine). Before evaluating these policies, the scenario implements rule refinement to lessen scale policies and adjust the sequence at the rule. During evaluation, the engine adopts a multi-cache mechanism that includes result cache, attribute cache, and policy cache to reduce the communication cost between engine and other components. To decrease matching magnitudes and enhance matching exactitudes, policy cache practices two stage index techniques. Finally, emulation tests validate that the overall evaluation performance of MLOBEE, using multi-level optimization technology, is better than most other similar systems.