Primary User Emulation in Cognitive Radio-Enabled WSNs for Structural Health Monitoring: Modeling and Attack Detection

Author:

Alcala’ Garrido Hassel Aurora1,Rivero-Angeles Mario E.1ORCID,Anaya Eleazar Aguirre2ORCID

Affiliation:

1. Network and Data Science Laboratory, CIC-Instituto Politecnico Nacional, Mexico City, Mexico

2. Cybersecurity Laboratory, CIC-Instituto Politecnico Nacional, Mexico City, Mexico

Abstract

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.

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Instrumentation,Control and Systems Engineering

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ensemble Regression Machine Learning Based Detection of Intrusion Packets in Healthcare Wireless Sensor Networks;2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE);2024-02-22

2. Teletraffic analysis of energy-efficient intruder detection using hash function techniques in images for remote monitoring in Wireless Sensor Networks;Computers and Electrical Engineering;2022-10

3. Defending against Internal Attacks in Healthcare-Based WSNs;Journal of Healthcare Engineering;2021-12-15

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