Deep learning approach for network intrusion detection systems

Abstract

As the network size is growing at a very fast rate, smart intrusion detection mechanisms need to be introduced. In a growing network, various unpredictable and unforeseen attacks are attacking the network and system, which harms both communication and information. Deep learning mechanisms are playing a vital role in various domains and providing recommendable results. Deep learning approaches are favorable for anomalies and exploitative groups of IDS. Various popular data sets in intrusion detection systems are discussed that are very useful in developing an effective and up-to-date tool to identify legitimate and illegitimate users for intrusion detection. In this chapter, a detailed study of deep learning-based approaches for intrusion detection systems has been presented.