Classification of artificial intelligence ids for smurf attack

نویسندگان

  • N. Ugtakhbayar
  • D. Battulga
  • Shirmen Sodbileg
چکیده

Many methods have been developed to secure the network infrastructure and communication over the Internet. 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 problem is amount of Intrusion which is increasing day by day. We need to know about network attack information using IDS, then analysing the effect. Due to the nature of IDSs which are solely signature based, every new intrusion cannot be detected; so it is important to introduce artificial intelligence (AI) methods / techniques in IDS. Introduction of AI necessitates the importance of normalization in intrusions. This work is focused on classification of AI based IDS techniques which will help better design intrusion detection systems in the future. We have also proposed a support vector machine for IDS to detect Smurf attack with much reliable accuracy.

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عنوان ژورنال:
  • CoRR

دوره abs/1202.1886  شماره 

صفحات  -

تاریخ انتشار 2012