Fuzzy K-Means Based Intrusion Detection System Using Support Vector Machine
Journal: International Journal of Science and Research (IJSR) (Vol.3, No. 8)Publication Date: 2014-08-05
Authors : Aman Mudgal; Rajiv Munjal;
Page : 1307-1310
Keywords : Intrusion Detection; Fuzzy K-Mean; SVM;
Abstract
Intrusion Detection System (IDS) is an important tool to identify various attacks to secure the networks. The goal of an Intrusion Detection System (IDS) is to provide a layer of defense against malicious users of computer systems by sensing a misuse and alerting operators to on-going attacks. Most real-world data, especially data available on the web, possess rich structural relationships. Most of the clustering algorithms neglect the structural relationships between the individual data types. We proposed Fuzzy K-Means clustering, which integrates two sources of information into a single clustering framework. Our main objective is to complete analysis of intrusion detection Dataset. In this paper we combine two of the efficient data mining algorithms and make a hybrid technique for the detection of intrusion called fuzzy k-means and Support vector machine.
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