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

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Hassel Aurora Alcala’ Garrido ◽  
Mario E. Rivero-Angeles ◽  
Eleazar Aguirre Anaya
Keyword(s):  
Cognitive Radio ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Performance Metrics ◽  
Average Energy ◽  
Primary User ◽  
Attack Detection ◽  
Additional Tool ◽  
Structural Health ◽  
Primary User Emulation

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.

scholarly journals Semi-supervised machine learning for primary user emulation attack detection and prevention through core-based analytics for cognitive radio networks

2019 ◽  
Vol 15 (9) ◽  
pp. 155014771986036 ◽  
Author(s):  
Sundar Srinivasan ◽  
KB Shivakumar ◽  
Muazzam Mohammad
Keyword(s):  
Machine Learning ◽  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Primary User ◽  
Radio Networks ◽  
Attack Detection ◽  
Supervised Machine Learning ◽  
Machine Language ◽  
Detection Accuracy ◽  
Primary User Emulation

Cognitive radio networks are software controlled radios with the ability to allocate and reallocate spectrum depending upon the demand. Although they promise an extremely optimal use of the spectrum, they also bring in the challenges of misuse and attacks. Selfish attacks among other attacks are the most challenging, in which a secondary user or an unauthorized user with unlicensed spectrum pretends to be a primary user by altering the signal characteristics. Proposed methods leverage advancement to efficiently detect and prevent primary user emulation future attack in cognitive radio using machine language techniques. In this paper novel method is proposed to leverage unique methodology which can efficiently handle during various dynamic changes includes varying bandwidth, signature changes etc… performing learning and classification at edge nodes followed by core nodes using deep learning convolution network. The proposed method is compared with that of two other state-of-art machine learning-based attack detection protocols and has found to significantly reduce the false alarm to secondary network, at the same time improve the overall detection accuracy at the primary network.

scholarly journals Performance analysis of a wireless sensor network with cognitive radio capabilities in structural health monitoring applications: A discrete model

2018 ◽  
Vol 14 (5) ◽  
pp. 155014771877400 ◽  
Author(s):  
Hassel Aurora Alcalá Garrido ◽  
Mario E Rivero-Angeles ◽  
Eleazar Aguirre Anaya ◽  
Felipe A Cruz-Perez ◽  
S Lirio Castellanos-Lopez ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Wireless Sensor Network ◽  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Time Slot ◽  
Wireless Sensor ◽  
Primary System ◽  
Structural Health ◽  
Analytical Approaches

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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