Selecting Features for Anomaly Intrusion Detection: A Novel Method using Fuzzy C Means and Decision Tree Classification

Jingping Song, Zhiliang Zhu, Peter Matthew David Scully, Christopher Price

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddTrafodion Cynhadledd (Nid-Cyfnodolyn fathau)

13 Dyfyniadau(SciVal)

Crynodeb

In this work, a new method for classification is proposed consisting of a combination of feature selection, normalization, fuzzy C means clustering algorithm and C4.5 decision tree algorithm. The aim of this method is to improve the performance of the classifier by using selected features. The fuzzy C means clustering method is used to partition the training instances into clusters. On each cluster, we build a decision tree using C4.5 algorithm. Experiments on the KDD CUP 99 data set shows that our proposed method in detecting intrusion achieves better performance while reducing the relevant features by more than 80%.
Iaith wreiddiolSaesneg
TeitlCyberspace Safety and Security
Is-deitlProceedings 5th International Symposium, CSS 2013, Zhangjiajie, China, November 13-15, 2013
GolygyddionGuojun Wang
CyhoeddwrSpringer Nature
Tudalennau299-307
Cyfrol8300
ISBN (Electronig)978-3-319-03584-0
ISBN (Argraffiad)978-3-319-03583-3, 3319035835
StatwsCyhoeddwyd - 11 Tach 2013

Cyfres gyhoeddiadau

EnwLecture Notes in Computer Science / Security and Cryptology
CyhoeddwrSpringer

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