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