UUM Repository | Universiti Utara Malaysian Institutional Repository
FAQs | Feedback | Search Tips | Sitemap

A detector generating algorithm for intrusion detection inspired by artificial immune system


Alsharafi, Walid Mohamed and Omar, Mohd Nizam (2015) A detector generating algorithm for intrusion detection inspired by artificial immune system. ARPN Journal of Engineering and Applied Sciences, 10 (2). pp. 608-612. ISSN 1819-6608

[img] PDF
Restricted to Registered users only

Download (236kB) | Request a copy

Abstract

Artificial immune system (AIS) allows us to inspire several ideas for the design of computer intrusion detection.The standard of negative selection algorithm (NSA), offered by Stephanie Forrest in 1994, is one of the most common mechanisms in AIS that applied in anomaly detection for the similarity of its basic idea. One of the most operational improvements in the standard of NSA is how to generate effective detectors which play a significant role in self and non-self discrimination in intrusion detection system (IDS).In this paper, we offer an improvement to a detector generating algorithm to generate effective detectors which leads to improve the standard of NSA, which in turn leads to improve the NSA based anomaly intrusion detection.Experimental results show that the improved algorithm able to generate more effective detectors and keeping the space and time complexities better than in the standard of NSA. This leads to detecting the real-time intrusion with less false negative.

Item Type: Article
Uncontrolled Keywords: detector, detector generating algorithm, negative selection, intrusion detection.
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Computing
Depositing User: Dr. Mohd. Nizam Omar
Date Deposited: 14 Jul 2015 07:57
Last Modified: 27 Apr 2016 01:08
URI: http://repo.uum.edu.my/id/eprint/14836

Actions (login required)

View Item View Item