吉林大学学报(工学版) ›› 2010, Vol. 40 ›› Issue (01): 171-0175.

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Distribute learning algorithm based on fuzzy C-means

WU Jing1,2,LIU Yan-heng1,2,LÜ| Rong1,2   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;2.Key Laboratory of Symbolic Computation and Knowledge Engineering|Ministry of Education, Jilin University, Changchun 130012, China
  • Received:2008-04-02 Online:2010-01-01 Published:2010-01-01

Abstract:

In intrusion detection in large-scale network, the accuracy of modular neural network learning algorithm is high but its efficiency is relatively low. In this paper, Self-Organizing Mapping (SOM) is adopted as a basic learning method to take the advantage of competitive characteristics of its neurons. Then Fuzzy C-Means (FCM) is introduced to carry out fusion learning and classification of the output weights of SOM. This method can not only maintain high accuracy of the SOM but also significantly reduce the learning time. The proposed method is tested using KDDCUP99 dataset. Results show that the detection rate of this method is high and its efficiency is improved.

Key words: computer application, intrusion detection, distribution learning, neural network, FCM

CLC Number: 

  • TP393.08
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