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IJSTR >> Volume 1 - Issue 11, December 2012 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Evaluation of Fuzzy K-Means And K-Means Clustering Algorithms In Intrusion Detection Systems

[Full Text]



Farhad Soleimanian Gharehchopogh, Neda Jabbari, Zeinab Ghaffari Azar



Index Terms:- Intrusion detection system, k-means, fuzzy k-means, clustering algorithm, Fuzzy IDS



Abstract:- According to the growth of the Internet technology, there is a need to develop strategies in order to maintain security of system. One of the most effective techniques is Intrusion Detection System (IDS). This system is created to make a complete security in a computerized system, in order to pass the Intrusion system through the firewall, antivirus and other security devices detect and deal with it. The Intrusion detection techniques are divided into two groups which includes supervised learning and unsupervised learning. Clustering which is commonly used to detect possible attacks is one of the branches of unsupervised learning. Fuzzy sets play an important role to reduce spurious alarms and Intrusion detection, which have uncertain quality.This paper investigates k-means fuzzy and k-means algorithm in order to recognize Intrusion detection in system which both of the algorithms use clustering method.



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