Title :
Design of Intrusion Detection Model Based on Data Mining Technology
Author_Institution :
Jiangmen Polytech., Jiangmen, China
Abstract :
This paper focuses on an improved FP-Growth algorithm. Preprocessing of data mining can increase efficiency on searching the common prefix of node and reduce the time complexity of building FP-tree. Based on the improved FP-Growth algorithm and other data mining techniques, an intrusion detection model is carried out. The experimental results demonstrate effectiveness of the improved algorithm and feasibility of intrusion detection model.
Keywords :
computational complexity; data mining; security of data; trees (mathematics); FP-growth algorithm; FP-tree; data mining technology; intrusion detection model; node common prefix; time complexity reduction; Algorithm design and analysis; Clustering algorithms; Computers; Data mining; Data models; Databases; Intrusion detection; FP-Growth algorithm; data mining; intrusion detection;
Conference_Titel :
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-1450-3
DOI :
10.1109/ICICEE.2012.156
