INSIGHTS OF FEATURE SELECTION IN IDS USING THE HYBRID PCALDA ALGORITHM

Abstract

The IDS is the very essential need for the digital communication to secure the data and to classify the connections as the normal or abnormal. The primary objective of the intrusion detection is to classify the connection. It is used to predict the model. There are various machine learning algorithms which will be used to predict the connection as the normal or abnormal. Machine learning algorithms are very useful in finding the solution for the difficult and challenging problem. In this various meta classifier algorithms are chosen and among them the best techniques are used for feature selection process in IDS.