|Table of Contents|

Network intrusion detection by using combination optimizingfeatures and classifier parameters(PDF)

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2017年01期
Page:
59-
Research Field:
Publishing date:

Info

Title:
Network intrusion detection by using combination optimizingfeatures and classifier parameters
Author(s):
Wang Zhanhong
Department of Police Technology,Railway Police College,Zhengzhou 450053,China
Keywords:
network intrusion feature selection classifier design biogeography-based optimization algorithm
PACS:
TP393.08
DOI:
10.14177/j.cnki.32-1397n.2017.41.01.008
Abstract:
In order to obtain better intrusion detection results,this paper designs a network intrusion detection algorithm by using combination optimizing features and classifier parameters.A mathematical model of combinatorial optimization is set up based on the features and parameters of classifier influence on intrusion detection results respectively.A biogeography-based optimization algorithm is adopted to simulate migration process of species inhabitancy to find the optimal solution of mathematical model and obtain the optimal features and classifier parameters.Standard intrusion detection-KDD Cup 99 data sets are used to test feasibility and superiority.The results show that the proposed algorithm can make mine relation between features and classifier parameters to improve intrusion detection rate and that the execution speed can meet the real-time requirements of intrusion detection.

References:

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Last Update: 2017-02-28