Artificial Intelligence Techniques for Network Intrusion Detection

Abstract

Network Intrusion has become the biggest concern of this generation. A lot of data is stored on commercial and personal computers. Protection and confidentiality of such information is very crucial for personnel in organizations which operate on classified data. This paper aims to study the different AI techniques that can be used in support of Intrusion (Anomaly and Misuse) Detection Systems to provide better Intrusion Detection & Prevention. This paper sheds light on techniques like ML, NEURAL NETWORK and Fuzzy Logic and how they can be coupled with INTRUSION DETECTION SYSTEM to detect attacks on private networks. It also provides other techniques which can be used for intrusion detection like Naïve Bayes, Decision Tree, K-nearest neighbors and Support Vector Machine. These techniques were used to classify malicious activity and normal activity and base rules such that necessary actions can be committed to alert and prevent intrusion.