Journals Proceedings

Abstract

Intrusion detection systems (IDSs) are an important component of defensive measures rotecting computer systems and networks from abuse. Due to the rising complexity and volume of the attacks in the network, Network Intrusion detection systems are preferred over Host based Intrusion detection systems. NIDS are categorized as misuse network intrusion detection and anomaly detection. Misuse detection systems deal with threats already known in beforehand. On the other hand, anomaly detection systems are more ambitious and try to discover new unknown threats. This paper focuses on anomaly based network intrusion detection systems. Such systems can detect intrusions by using various Techniques such as statistical, knowledge based or machine learning. This paper describes a contemporary overview of the machine learning techniques for anomaly based network intrusion detection system.