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Summary:The global view of firewall policy conflict is important for administrators to optimize the policy.It has been lack of appropriate firewall policy global conflict analysis,existing methods focus on local conflict detection.We research the global conflict detection algorithm in this paper.We presented a semantic model that captures more complete classifications of the policy using knowledge concept in rough set.Based on this model,we presented the global conflict formal model,and represent it with OBDD(Ordered Binary Decision Diagram).Then we developed GFPCDA(Global Firewall Policy Conflict Detection Algorithm) algorithm to detect global conflict.In experiment,we evaluated the usability of our semantic model by eliminating the false positives and false negatives caused by incomplete policy semantic model,of a classical algorithm.We compared this algorithm with GFPCDA algorithm.The results show that GFPCDA detects conflicts more precisely and independently,and has better performance.
Bibliography:The global view of firewall policy conflict is important for administrators to optimize the policy.It has been lack of appropriate firewall policy global conflict analysis,existing methods focus on local conflict detection.We research the global conflict detection algorithm in this paper.We presented a semantic model that captures more complete classifications of the policy using knowledge concept in rough set.Based on this model,we presented the global conflict formal model,and represent it with OBDD(Ordered Binary Decision Diagram).Then we developed GFPCDA(Global Firewall Policy Conflict Detection Algorithm) algorithm to detect global conflict.In experiment,we evaluated the usability of our semantic model by eliminating the false positives and false negatives caused by incomplete policy semantic model,of a classical algorithm.We compared this algorithm with GFPCDA algorithm.The results show that GFPCDA detects conflicts more precisely and independently,and has better performance.
firewall policy semantic model conflict analysis conflict detection
11-5439/TN
ISSN:1673-5447
DOI:10.1109/CC.2014.6880468