Survey of learning methods in intrusion detection systems

Intrusion Detection System (IDS) is an essential method to protect network security from incoming on-line threats. Machine learning enable automates the classification of network patterns. This paper review the learning and detection methods in IDS, discuss the problems with existing intrusion detection systems and review data reduction techniques used in IDS in order to deal with huge volumes of audit data. Finally, conclusion and recommendation are included.