Title :
Application of Network Intrusion Detection Based on Fuzzy C-Means Clustering Algorithm
Author :
Ren, Wuling ; Cao, Jinzhu ; Wu, Xianjie
Author_Institution :
Coll. of Comput. & Inf. Eng., Zhejiang Gongshang Univ., Hangzhou, China
Abstract :
Aiming at the problem of higher false positive and missing report rate in network intrusion detection, an intrusion detection method based on clustering algorithm is proposed in this paper. This method applies Fuzzy C-means clustering Algorithm to the detection of network intrusion. Through the building of intrusion detection model, carries out fuzzy partition and the clustering of data, and this will detach normal data and attack data effectively. The experiment shows the feasibility and validity of Fuzzy C-means clustering algorithm.
Keywords :
pattern clustering; security of data; data clustering; fuzzy C-means clustering algorithm; fuzzy partition; network intrusion detection; Application software; Clustering algorithms; Computer networks; Educational institutions; Face detection; Fuzzy set theory; Fuzzy sets; Intrusion detection; Partitioning algorithms; Protection; Fuzzy C-means; K-means; Network intrusion detection; Soft partition; fuzzy clustering;
Conference_Titel :
Intelligent Information Technology Application, 2009. IITA 2009. Third International Symposium on
Conference_Location :
Nanchang
Print_ISBN :
978-0-7695-3859-4
DOI :
10.1109/IITA.2009.269