Improved Association Rule Mining Algorithm and Its Applications in Intrusion Detection
Haibin Huang · Computer Technology and Development · 2011
The FP-Growth algorithm based on FP-Tree needs to create a large number of conditional FP-Trees recursively in the process of mining frequent patterns.It is not efficient and not good to apply in intrusion detection,in which the association rules mining include many elements.Because the intrusion includes many methods and elements,must quantitatively analyse intrusion samples.It analyzes the features of intrusion detection,proposed a new frequent pattern tree CP-Tree based on conditional frequent-items and the improved algorithms MineCPT which directly mines in the tree.Theoretical analysis and experimental results show that the MineCPT algorithm is superior to FP-Growth algorithm in memory occupancy and reliability.It has achieved better results in the field of intrusion detection.