Artificial Intelligence Based Intrusion Detection Techniques - A Review

The Internet connects hundreds of millions of computers across the world running on multiple hardware and software platforms providing communication and commercial services. However, this interconnectivity among computers also enables malicious users to misuse resources and mount Internet attacks. Continuously developing Internet attacks poses a severe challenge to develop a flexible, adaptive security oriented methods. Now a day most of commercially available intrusion detection systems are signature based. These systems perform well in detecting known attacks whose signature resides in the database. Such systems require frequent rule-base updates and signature updates, and are not capable of detecting unknown attacks. For detection of known and zero day unknown attacks, anomaly based network intrusion detection systems are best approaches. Anomaly based techniques are conceptually very attractive but many problems remains to be solved before being adapted widely. Problems including false alarm rate, detection accuracy and failure to scale high speed etc. still need to be solved. In this text, we review Artificial Intelligence based intrusion detection techniques.