Abstract
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.
Highlights
A wireless sensor network is a network of cheap and simple processing autonomous devices that are spatially distributed in an area of interest in order to cooperatively monitor physical or environmental phenomena
As identified in [4,5,6], wireless sensor networks (WSNs) are susceptible to various types of attacks or to node compromises that exploit known and unknown vulnerabilities of protocols, software, and hardware, and threaten the security, integrity, authenticity, and availability of data that reside in these networked systems
To reduce the energy overheads, the genetic algorithm (GA)-based scheme presented in [28] benefits from the hierarchical structure of the network arranging the primary computing tasks to the base station
Summary
A wireless sensor network is a network of cheap and simple processing autonomous devices (called sensor nodes) that are spatially distributed in an area of interest in order to cooperatively monitor physical or environmental phenomena. The present work contributes to the area of wireless sensor network security by proposing a novel anomaly-based detection and location-attribution algorithm for cluster-based UWB WSNs, named ADLU. The proposed algorithm has dedicated procedures for secure cluster formation, periodic re-clustering, and efficient cluster member monitoring It exploits the peculiar characteristics of the UWB PHY defined in the IEEE 802.15.4 standard [1] in order to facilitate the anomaly detection and location attribution processes. To reduce the energy overheads, the genetic algorithm (GA)-based scheme presented in [28] benefits from the hierarchical structure of the network arranging the primary computing tasks to the base station (recall that the base station has much softer limitations for power and computation) While this scheme is not directly concerned with detection, it could assist detection schemes in advancing their performance and efficiency by optimizing, for instance, the placement of the monitoring nodes.
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