DocumentCode :
1822286
Title :
Research on Intrusion Detection Based on an Improved SOM Neural Network
Author :
Jiang, Dianbo ; Yang, Yahui ; Xia, Min
Author_Institution :
Sch. of Software & Microelectron., Peking Univ., Beijing, China
Volume :
1
fYear :
2009
fDate :
18-20 Aug. 2009
Firstpage :
400
Lastpage :
403
Abstract :
Neural networks approach is an advanced methodology used for intrusion detection. As a type of neural network, Self-organizing Maps (SOM) is getting more attention in the field of intrusion detection. In this paper, some improvements on SOM algorithm are made in order to increase detection rate and improve the stability of intrusion detection, include: (1) Modify the strategy of ldquowinner-take-allrdquo to decrease underutilized or completely unutilized neurons. (2) Introduce interaction weight which describes the effect between each neuron in the output layer to enhance the relationships between the input pattern and the weights of all the nodes when adjusting weights; The improved SOM is implemented and applied to the intrusion detection. The validities and feasibilities of the improved SOM are confirmed through experiments on KDD Cup 99 datasets. The experiment result shows that the detection rate has been increased by employing the improved SOM.
Keywords :
neural nets; security of data; intrusion detection; neural network; self-organizing maps; Biological neural networks; Computer networks; Internet; Intrusion detection; Neural networks; Neurons; Protection; Self organizing feature maps; Stability; Supervised learning; Improved SOM; Intrusion Detection; Self-organizing Maps;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-0-7695-3744-3
Type :
conf
DOI :
10.1109/IAS.2009.247
Filename :
5284114
Link To Document :
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