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

Comparison of Machine Learning algorithms performance in detecting network intrusion

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)
Abd Jalil, K. ; Fac. of Comput. & Math. Sci., Univ. Teknol. MARA, Shah Alam, Malaysia ; Kamarudin, M.H. ; Masrek, M.N.

Organization has come to realize that network security technology has become very important in protecting its information. With tremendous growth of internet, attack cases are increasing each day along with the modern attack method. One of the solutions to this problem is by using Intrusion Detection System (IDS). Machine Learning is one of the methods used in the IDS. In recent years, Machine Learning Intrusion Detection system has been giving high accuracy and good detection on novel attacks. In this paper the performance of a Machine Learning algorithm called Decision Tree (J48) is evaluated and compared with two other Machine Learning algorithms namely Neural Network and Support Vector Machines which has been conducted by A. Osareh [1] for detecting intrusion. The algorithms were tested based on accuracy, detection rate, false alarm rate and accuracy of four categories of attacks. From the experiments conducted, it was found that the Decision tree (J48) algorithm outperformed the other two algorithms.

Published in:

Networking and Information Technology (ICNIT), 2010 International Conference on

Date of Conference:

11-12 June 2010

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.