Mining Frequent Patterns in Network Intrusion Detection
网络入侵检测系统中的频繁模式挖掘*

In the network intrusion detection, Apriori algorithm is used to extract relative rules, but its processing precision and efficiency are not satisfactory. In order to resolve the problem, based on FP-growth, this paper proposes a new algorithm named PFP-growth, this algorithm applies an idea of divide and rule, makes good use of FP-tree, and eases the load of system when mining a large database, which makes its velocity improved obviously. Besides we design a new method to set min-support, which makes frequent patterns mined much precise.