سال انتشار: ۱۳۸۴

محل انتشار: یازدهمین کنفرانس سالانه انجمن کامپیوتر ایران

تعداد صفحات: ۶

نویسنده(ها):

Adel Nadjaran Toosi – Communication and Computer Research Lab. Faculty of Engineering,Ferdowsi University of Mashhad
Mohsen Kahani – Computer Engineering Department, Faculty of Engineering,Ferdowsi University of Mashhad

چکیده:

Computer networks have experienced an explosive growth over the past few years and have become the targets for hackers and intruders. An intrusion detection system’s main goal is to classify activities of a system into two major categories: normal activity and suspicious or intrusive activity. The objective of this paper is to expose ANFIS as a neuro-fuzzy classifier to detect intrusions in computer networks. Our experiments and evaluations were performed with the KDD Cup 99 intrusion detection dataset which is a version of the 1998 DARPA intrusion detection evaluation dataset prepared and managed by MIT Lincoln Laboratories. This paper shows that our proposed method can be effective in detecting various intrusions