Paper Title:
Research for SVM with Self-Reacting Feature Weighted in IDS
  Abstract

Studying technology of feature analysis, a new method of feature selection based on self -reacting feature weighted is presented, and it is applied into the intrusion feature selection with the technique of feature selection and the technique of SVM classification combined. The method can reduce the time complexity and space complexity with the situation of parameter trying improved. The experiment results show that the detection precision rises obviously, meanwhile, the training time and the test time are also improved variously. The model has the ability to respond quickly with the accuracy and real-time performance of the Intrusion Detection System improved effectively. So, the method can be extended significantly.

  Info
Periodical
Advanced Materials Research (Volumes 204-210)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
604-607
DOI
10.4028/www.scientific.net/AMR.204-210.604
Citation
Q. Yu, S. Wang, J. L. Wang, B. H. Zhang, "Research for SVM with Self-Reacting Feature Weighted in IDS", Advanced Materials Research, Vols. 204-210, pp. 604-607, 2011
Online since
February 2011
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Price
$32.00
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