An Analysis of Intrusion Detection using Machine Learning Techniques

Abstract

intrusion detection system (IDS) tracks network traffic in pursuit of unusual behaviour that may be an attack or unauthorized access. Current technologies have been designed to detect known threats but are unable to identify new menaces. Through base lining the network, they most often identify known threats based on established rules or behavioural analysis. A sophisticated attacker may circumvent these strategies, and the need for better intrusion detection is increasing by the day This paper explains the comparative performance of intrusion prevention learning methods, i.e. accurate detection, incorrect emergency alert rate etc.