Novel hybrid intrusion detection system for clustered wireless sensor network

TL;DR

This paper introduces a hybrid intrusion detection system for clustered wireless sensor networks that combines anomaly detection using support vector machines with misuse detection, effectively identifying routing attacks with low false alarms.

Contribution

It presents a novel hybrid framework integrating SVM-based anomaly detection and misuse detection specifically for clustered WSNs, improving security.

Findings

Most routing attacks detected successfully

Low false alarm rate achieved

Effective security mechanism for WSNs

Abstract

Wireless sensor network (WSN) is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the network. It is widely known, that the intrusion detection is one of the most efficient security mechanisms to protect the network against malicious attacks or unauthorized access. In this paper, we propose a hybrid intrusion detection system for clustered WSN. Our intrusion framework uses a combination between the Anomaly Detection based on support vector machine (SVM) and the Misuse Detection. Experiments results show that most of routing attacks can be detected with low false alarm.