A novel mutual feature CRF for intrusion detection system
by Jinny S. Vinila; J. Jayakumari
International Journal of Enterprise Network Management (IJENM), Vol. 6, No. 4, 2015

Abstract: Intrusion detection system (IDS) is a system that monitors the network to find out the suspicious activity there by stopping the disruption that can be caused by intruders. Disruption caused by intruders can be stopped by having effective IDS. Intrusion detection system has three works, i.e., it continuously monitors network, compares with knowledge base and gives alarm to the administrator. The effectiveness of the system resides on the knowledge base. Preparing knowledge base is the most required part. This can be simply thought as a data analysis system. Data mining algorithms are applied to develop the knowledge base. Mining algorithm alone will not produce best knowledge base and so an additional step is required to sharp the algorithm. In this paper, we propose a mutual information feature selection algorithm with conditional random field, which produces high performance, less false positive IDS.

Online publication date: Sun, 27-Dec-2015

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 Enterprise Network Management (IJENM):
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