Feature Analysis for Intrusion Detection in Mobile Ad-hoc Networks

As Mobile Ad-hoc network (MANET) has become a very importanttechnology, research concerning its security problem, especially,in intrusion detection has attracted many researchers. Featureselection methodology plays a central role in the data analysisprocess. The proposed features are tested in different networkoperating conditions. PCA is used to analyze the selectedfeatures. This is because, redundant and irrelevant features oftenreduce performance of the detection system. Performance reductionwill occur both in speed and predictive accuracy. This paper aimsto select and analyze the network features using principalcomponent analysis. In this paper, performing various experiments,normal and attack states are simulated and the results for theselected features are analyzed.