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There are many risks of network attacks under the Internet environment, internet security is a vital issue and therefore, the intrusion detection is one major research problem for business and personal networks to resist external attacks. The goal of Intrusion Detection Systems (IDSs) is to provide a wall of defense to confront the attacks of computer systems on Internet where the conventional firewall do not succeeds. In this paper, comparison of most commonly used machine learning techniques based on genetic algorithm, support vector machines, artificial neural networks, etc. in intrusion detection domain, has been made. A comparative analysis of these techniques to detect intrusions in host and networks has also been made.
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