International Journal of Emerging Trends & Technology in Computer Science (IJETTCS)
Feature selection is an indispensable pre-processing step when mining huge datasets that can significantly improve the overall system performance. The filter phase select the features with highest information gain and this reduced feature subset is then passed to k-means clustering to identify normal and attack classes. This paper describes about a method of intrusion detection that uses machine learning algorithms. Here the authors discuss about the combinational use of two machine learning algorithms called information gain based feature selection and K-means clustering algorithm.