Welcome to the InfoSci Platform
Reference Hub2
An Enhanced Fuzzy ARM Approach for Intrusion Detection

An Enhanced Fuzzy ARM Approach for Intrusion Detection

Nasser S. Abouzakhar, Huankai Chen, Bruce Christianson
Copyright: © 2011 |Volume: 3 |Issue: 2 |Pages: 21
ISSN: 1941-6210|EISSN: 1941-6229|EISBN13: 9781613506462|DOI: 10.4018/jdcf.2011040104
Cite Article Cite Article

MLA

Abouzakhar, Nasser S., et al. "An Enhanced Fuzzy ARM Approach for Intrusion Detection." IJDCF vol.3, no.2 2011: pp.41-61. http://doi.org/10.4018/jdcf.2011040104

APA

Abouzakhar, N. S., Chen, H., & Christianson, B. (2011). An Enhanced Fuzzy ARM Approach for Intrusion Detection. International Journal of Digital Crime and Forensics (IJDCF), 3(2), 41-61. http://doi.org/10.4018/jdcf.2011040104

Chicago

Abouzakhar, Nasser S., Huankai Chen, and Bruce Christianson. "An Enhanced Fuzzy ARM Approach for Intrusion Detection," International Journal of Digital Crime and Forensics (IJDCF) 3, no.2: 41-61. http://doi.org/10.4018/jdcf.2011040104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The integration of fuzzy logic with data mining methods such as association rules has achieved interesting results in various digital forensics applications. As a data mining technique, the association rule mining (ARM) algorithm uses ranges to convert any quantitative features into categorical ones. Such features lead to the sudden boundary problem, which can be smoothed by incorporating fuzzy logic so as to develop interesting patterns for intrusion detection. This paper introduces a Fuzzy ARM-based intrusion detection model that is tested on the CAIDA 2007 backscatter network traffic dataset. Moreover, the authors present an improved algorithm named Matrix Fuzzy ARM algorithm for mining fuzzy association rules. The experiments and results that are presented in this paper demonstrate the effectiveness of integrating fuzzy logic with association rule mining in intrusion detection. The performance of the developed detection model is improved by using this integrated approach and improved algorithm.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.