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

Optimization of membership functions in anomaly detection based on fuzzy data mining

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

2 Author(s)
Tian-Qing Zhu ; Dept. of Comput. Inf. Eng., Wuhan Polytech. Univ., China ; Ping Xiong

Association rules mining is an effective method to extract hidden knowledge in databases that is used widely in intrusion detection. But it causes the sharp boundary problem in handling databases with quantitative attributes. To solve the problem, a method is presented that integrates fuzzy sets and genetic algorithm in anomaly detection. Encoding the parameters of membership functions into an individual (chromosome) and embedding the fuzzy association rules mining techniques into the genetic optimization, an optimal parameter-set can be obtained. With the use of the parameter-set in anomaly detection, the normal states of protected system can be differentiated from the anomalous states to the largest extent, and the veracity of anomaly detection is improved significantly.

Published in:

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on  (Volume:4 )

Date of Conference:

18-21 Aug. 2005

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.