Feature extraction using Deep Learning for Intrusion Detection System

Abstract

Deep Learning is an area of Machine Learning research, which can be used to manipulate large amount of information in an intelligent way by using the functionality of computational intelligence. A deep learning system is a fully trainable system beginning from raw input to the final output of recognized objects. Feature selection is an important aspect of deep learning which can be applied for dimensionality reduction or attribute reduction and making the information more explicit and usable. Deep learning can build various learning models which can abstract unknown information by selecting a subset of relevant features. This property of deep learning makes it useful in analysis of highly complex information one which is present in intrusive data or information flowing with in a web system or a network which needs to be analyzed to detect anomalies. Our approach combines the intelligent ability of Deep Learning to build a smart Intrusion detection system.