Comparative analysis of various Machine Learning Techniques for Intrusion Detection System

Surfing internet becomes common now-a-days that gave a chance for intruders to steal information. Therefore security is very important to detect any unwanted activities by using intrusion detection system. Intrusion detection system is one of the vast new technologies in this decade which makes the system to learn by itself and predict the values using machine learning techniques. To analyze intrusion detection system for detecting network attacks using various machine learning techniques has been proposed in this paper. Machine learning algorithms such as J48, Naive Bayes, Random Forest and REP tree are compared using Kddcup99 dataset. When comparing these machine learning algorithms in which random forest gives high detection rate.