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Author:

Tian, Li-Ye (Tian, Li-Ye.) | Liu, Wei-Peng (Liu, Wei-Peng.)

Indexed by:

EI Scopus

Abstract:

An incremental intrusion detecting model is proposed in this paper. This model integrates unsupervised Self Organizing Map and supervised Radial Basis Function to complete incremental learning. Self Organizing Map can get new type intrusion information and generate new nodes in Radial Basis Function. By this model, intrusion of unknown type can be detected online. Experiment results show our model could detect new type intrusions without forgetting the old ones. © 2010 IEEE.

Keyword:

Functions Conformal mapping Supervised learning Intrusion detection Self organizing maps Radial basis function networks Neural networks

Author Community:

  • [ 1 ] [Tian, Li-Ye]Dept. of Electronic and Information Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China
  • [ 2 ] [Tian, Li-Ye]Trusted Computing Lab., College of Computer, Beijing University of Technology, Beijing 100022, China
  • [ 3 ] [Liu, Wei-Peng]State Key Laboratory of Information Security, GUCAS, Beijing 100039, China
  • [ 4 ] [Liu, Wei-Peng]Trusted Computing Lab., College of Computer, Beijing University of Technology, Beijing 100022, China

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Source :

Year: 2010

Volume: 6

Page: 2849-2853

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 8

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 13

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