Feature Reduction in MANET using Machine Learning Language

Abstract

Mobile ad-hoc network (MANET) is an infrastructure-less network. Therefore, MANET involves a selection of exact security schemes to notice the false entrance of the mischievous nodes. Along these lines, we require solid instrument to identify these pernicious nodes and to arrange ordinary and irregular nodes based on the conduct or performance of nodes. Machine learning system nowadays used to built a best IDS for recognizing exception or misbehaving nodes rapidly and precisely give grouping by watching conduct of those nodes in the system. In MANET system, numbers of parameters are taken for analysation. It makes the IDS system complex. To avoid this complexity many techniques are derived for feature reduction. In this proposed work, we are testing how feature reduction can be done using Python machine learning program.