Cart (Loading....) | Create Account
Close category search window

Improved Detection Approach for Distributed Denial of Service Attack Based on SVM

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

3 Author(s)
Xiang Xu ; Sch. of Mech. & Mater., China Three Gorges Univ., Yichang, China ; Ding Wei ; Yuelei Zhang

The intrusion detection rate is greatly influenced by the parameters of the support vector machine (SVM) model. In order to overcome the parameter limits to improve the identify accuracy of Distributed Denial of Service (DDoS) attack, this paper presents a new detection method based on Kernel Principle Component Analysis (KPCA) and Particle Swarm Optimization (PSO)-Support Vector Machine (SVM). The KPCA was used to obtain the important characteristics of the intrusion data to eliminate the redundant features. Then the PSO was used to optimize the SVM parameters. Experimental results show the proposed approach can enhance the detection rate, and performs better than the PCA based methods.

Published in:

Circuits, Communications and System (PACCS), 2011 Third Pacific-Asia Conference on

Date of Conference:

17-18 July 2011

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.