XACML policy evaluation optimization research based on attribute weighted clustering and statistics reordering | IEEE Conference Publication | IEEE Xplore

XACML policy evaluation optimization research based on attribute weighted clustering and statistics reordering


Abstract:

In order to improve the efficiency of policy evaluation, the paper proposes a scheme of evaluation optimization. The scheme adopts policy reordering and clustering strate...Show More

Abstract:

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.
Date of Conference: 18-20 July 2017
Date Added to IEEE Xplore: 23 October 2017
ISBN Information:
Conference Location: Macao, China

Contact IEEE to Subscribe

References

References is not available for this document.