Intrusion detection and prevention systems: A review

Abstract

In this paper, the various methods for intrusion detection and prevention are discussed based on the four review papers. In the first paper, the support vector machines and decision trees machine learning techniques are being used to train the data set for detecting DOS attacks in WSN and found that decision trees are more efficient than support vector machines. In the second paper, the routing attacks such as sinkhole and selective forwarding are being detected in the Internet of things for which two detection and prevention algorithms, i.e. key match algorithm (KMA) and cluster-based algorithm (CBA) are used. Same intrusion detection and prevention system which is developed for wired networks cannot be used for wireless networks. In the third paper, a system called wireless intrusion detection prevention and attack system `WIDPAS' is proposed which attacks the attacker and sends warning to the administrator. In the fourth paper, a method is used which uses filter firewall, honeypot intrusion detection, anomaly intrusion detection and prevention firewall to protect an organization’s network.