XACML policy evaluation optimization research based on attribute weighted clustering and statistics reordering
Pan Jun Sun · 2017
In order to improve the efficiency of policy evaluation, the paper proposes a scheme of evaluation optimization. The scheme adopts policy reordering and clustering strategies to optimize policy procession. During evaluation, the scheme proposes to merge algorithm combined with policy priority assessment, preferably selects the satisfied policies and rules to improve the matching speed. The experimental results show that our approach reduces the matching operation and improves the efficiency of evaluation.