Nowadays, the use of sensor nodes for the IoT is widespread. At the same time, cyberattacks on these systems have become a relevant design consideration in the practical deployment of wireless sensor networks (WSNs). However, there are some types of attacks that have to be prevented or detected as fast as possible, like, for example, attacks that put lives in danger. In this regard, a primary user emulation (PUE) attack in a structural health monitoring (SHM) system falls inside this category since nodes failing to report structural damages may cause a collapse of the building with no warning to people inside it. Building on this, we mathematically model an energy and resource utilization-efficient WSN based on the cognitive radio (CR) technique to monitor the SHM of buildings when a seismic activity occurs, making efficient use of scarce bandwidth when a PUE attack is in progress. The main performance metrics considered in this work are average packet delay and average energy consumption. The proposed model allows an additional tool for the prompt identification of such attacks in order to implement effective countermeasures.
This article studies the performance of a wireless sensor network with cognitive radio capabilities to gather information about structural health monitoring of buildings in case of seismic activity. Since the use of the local area network is intensive in office and home environments, we propose the use of empty cellular channels (primary system). As such, the structural health monitoring does not degrade the local communications. Thus, the wireless sensor network for structural health monitoring acts as secondary network. Two discrete-time analytical approaches are proposed and developed to evaluate the system performance in terms of both the average packet delay and average energy consumption. The first one is an approximation suitable for the case when the time slot duration is small relative to the mean call inter-arrival time. The second model is accurate for any time slot duration and inter-arrival times.
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