By Topic

A Synthetic Dimension Reduction in Intrusion Detection System

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Zhang Changyou ; Sch. of Comput. & Inf., Shijiazhuang Railway Inst., Shijiazhuang, China ; Wang Yumei ; Piao Chunhui ; Yu Jiong

In order to improve the performance of Intrusion Detection System (IDS), a synthetic dimension reduction method is proposed in this paper. First of all, we define a similarity distance algorithm between two vectors based on analogy reasoning. Then, the merit of the synthetic dimension reduction is analyzed in a 3-dimension space. Finally, the distances between a new behavior sample which is sniffered from network and behavior sample sets. Finally, using these two distances as ordinate and abscissa, this new behavior sample is mapped into a point in a two-dimensional coordinates plane from a multi-dimensional vector space. According to the location of this point, an behavior can be determined whether it is a intrusion.

Published in:

Security Technology, 2008. SECTECH '08. International Conference on

Date of Conference:

13-15 Dec. 2008