Intrusion Detection using Artificial Neural Network

Abstract

Intrusion Detection is the task of detecting, preventing and possibly reacting to the attack and intrusions in a network based computer systems. In the literature several machine-learning paradigms have been proposed for developing an Intrusion Detection System. This paper proposes an Artificial Neural Network approach for Intrusion Detection. A Feed Forward Neural Network trained by Back Propagation algorithm is developed to classify the intrusions using a profile data set (ten percent of the KDD Cup 99 Data) with the information related to the computer network during Normal behavior and during Intrusive (Abnormal) behavior. Test result shows that the proposed approach works well in detecting different attacks accurately with less false positive and negative rate and it is comparable to those reported in the literature.