Intrusion Detection Based on RBF Neural Network

Radial basis function (RBF) has been one of the most common neural networks used in the intrusion detection system (IDS). To improve the approximation performance and calculation speed of RBF, we describe a method to deal with the benchmark datasets adopted in the research. It includes converting th...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Jing Bi, Kun Zhang, Xiaojing Cheng
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Civil engineering Computer networks Data mining Electronic commerce Event detection Feedforward neural networks Intrusion detection Military standards Network Security Neural networks Radial basis function networks RBF network
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Beschreibung
Zusammenfassung:	Radial basis function (RBF) has been one of the most common neural networks used in the intrusion detection system (IDS). To improve the approximation performance and calculation speed of RBF, we describe a method to deal with the benchmark datasets adopted in the research. It includes converting the string to numeric elements firstly, then omitting the unnecessary data and ensuring that the data has the reasonable range limit. The simulation results built upon Matlab software show that the RBF neural network has better performance than BP neural network.
DOI:	10.1109/IEEC.2009.80