Anomaly detection and localization in 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. WSNs are vulnerable to various types of attacks, and as such, they require mechanisms to defend against them. Several anomaly detection algorithms have been proposed to date as a solution to the problem. However, none of them is specifically designed for the ultra-wideband (UWB) technology. UWB is a key solution for wireless connectivity characterized by ultra low power consumption, and high precision ranging. Based on these principles, we propose a novel anomaly detection and localization algorithm for cluster-based UWB wireless sensor networks. Towards securing the cluster formation protocol, we also define a novel, trust-aware leader election metric. The performance of the proposed algorithm in identifying intrusions using a rule-based detection technique is studied via simulations.