Intrusion Detection System Using Weka Data Mining Tool
Journal: International Journal of Science and Research (IJSR) (Vol.3, No. 5)Publication Date: 2014-05-15
Authors : Asma Abbas Hassan; Alaa F. Sheta; Talaat M. Wahbi;
Page : 337-342
Keywords : intrusion detection; Naive bayes; Decision Trees; Random Forest; Random Tree; Confusion Matrix;
Abstract
Traditional intrusion prevention techniques, such as firewalls, access control or encryption, have failed to fully protect networks and systems from increasing attacks. Therefore an intrusion detection system (IDS) has become an important component of security infrastructure and a key part of system defense to detect these attacks before they make a disaster in the system. In this paper, we are going to design an intrusion detection system using Weka Data Mining Software, to check the existence of intrusion, and classify it when detected, to know the type of intrusion, according to attack types, this will implemented in Weka 3.6 Software, with KDD CUP 99 intrusion detection dataset. We construct a system with a very accurate, flexible and effective results when compare with other systems
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