Share Email Print
cover

Proceedings Paper

A study on fuzzy intrusion detection
Author(s): Jing Tao Yao; Song Lun Zhao; Larry V. Saxton
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Current intrusion detection techniques mainly focus on discovering abnormal system events in computer networks and distributed communication systems. Clustering techniques are normally utilized to determine a possible attack. Due to the uncertainty nature of intrusions, fuzzy sets play an important role in recognizing dangerous events and reducing false alarms level. This paper proposes a dynamic approach that tries to discover known or unknown intrusion patterns. A dynamic fuzzy boundary is developed from labelled data for different levels of security needs. Using a set of experiment, we show the applicability of the approach.

Paper Details

Date Published: 28 March 2005
PDF: 8 pages
Proc. SPIE 5812, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005, (28 March 2005); doi: 10.1117/12.604465
Show Author Affiliations
Jing Tao Yao, Univ. of Regina (Canada)
Song Lun Zhao, Univ. of Regina (Canada)
Larry V. Saxton, Univ. of Regina (Canada)


Published in SPIE Proceedings Vol. 5812:
Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005
Belur V. Dasarathy, Editor(s)

© SPIE. Terms of Use
Back to Top