Enhanced relevant feature selection model for intrusion detection systems
by Ayman I. Madbouly; Tamer M. Barakat
International Journal of Intelligent Engineering Informatics (IJIEI), Vol. 4, No. 1, 2016

Abstract: With the increased amount of network threats and intrusions, finding an efficient and reliable defence measure has a great focus as a research field. Intrusion detection systems (IDSs) have been widely deployed as effective defence measure for existing networks. IDSs detect anomalies based on features extracted from network traffic. Network traffic has many features to measure. The problem is that with the huge amount of network traffic we can measure many irrelevant features. These irrelevant features usually affect the performance of detection rate and consume the IDSs resources. In this paper, we proposed an enhanced model to increase attacks detection accuracy and to improve overall system performance. We measured the performance of the proposed model and verified its effectiveness and feasibility by comparing it with nine-different models and with a model that used the 41-features dataset. The results showed that, our enhanced model could efficiently achieves high detection rate, high performance rate, low false alarm rate, and fast and reliable detection process.

Online publication date: Tue, 02-Feb-2016

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Intelligent Engineering Informatics (IJIEI):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com