Bagging Ensemble Technique for Intrusion Detection System
Today almost no one can exclude himself or herself from using the Internet. Intrusion Detection System (IDS) is software which helps the user to protect their system from other system when other person tries to access their network. It secures their system resources without giving access to other system. This paper discusses intrusion detection systems built using ensemble techniques, i.e., by combining several machine learning algorithms. Network attacks can be divided into four classes: probe, remote to local, denial of service, and user to root. Experiments showed that Intrusion Detection Systems (IDS) obtain better results when each class of attacks is treated as a separate problem by ensemble approach and handled by some specialized algorithms.