%0 Journal Article
%T CLASSIFICATION OF ARTIFICIAL INTELLIGENCE IDS FOR SMURF ATTACK
%A N.Ugtakhbayar
%A D.Battulga
%A Sh.Sodbileg
%J International Journal of Artificial Intelligence & Applications
%D 2012
%I Academy & Industry Research Collaboration Center (AIRCC)
%X Many methods have been developed to secure the network infrastructure and communication over theInternet. Intrusion detection is a relatively new addition to such techniques. Intrusion detection systems(IDS) are used to find out if someone has intrusion into or is trying to get it the network. One big problemis amount of Intrusion which is increasing day by day. We need to know about network attack informationusing IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every newintrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniquesin IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focusedon classification of AI based IDS techniques which will help better design intrusion detection systems in thefuture. We have also proposed a support vector machine for IDS to detect Smurf attack with much reliableaccuracy.
%K Classification
%K Decision Tree
%K Smurf attack
%K Intelligence IDS
%K IDS
%U http://airccse.org/journal/ijaia/papers/3112ijaia04.pdf