ADLU: a novel anomaly detection and location-attribution algorithm for UWB wireless sensor networks
Wireless sensor networks (WSNs) are gaining more and more interest in the research community due to their unique characteristics. Besides energy consumption considerations, security has emerged as an equally important aspect in their network design. This is because WSNs are vulnerable to various types of attacks and to node compromises, and as such, they require security mechanisms to defend against them. An intrusion detection system (IDS) is one such solution to the problem. While several signature-based and anomaly-based detection algorithms have been proposed to date for WSNs, none of them is specifically designed for the ultra-wideband (UWB) radio technology. UWB is a key solution for wireless connectivity among inexpensive devices characterized by ultra-low power consumption and high precision ranging. Based on these principles, in this paper, we propose a novel anomaly-based detection and location-attribution algorithm for cluster-based UWB WSNs. The proposed algorithm, abbreviated as ADLU, has dedicated procedures for secure cluster formation, periodic re-clustering, and efficient cluster member monitoring. The performance of ADLU in identifying and localizing intrusions using a rule-based anomaly detection scheme is studied via simulations.
wireless sensor networks anomaly-based detection uwb radio technology security in uwb wsns attack attribution ranging attacks