A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks

Khan, Muhammad Sajjad; Faisal, Mohammad; Kim, Su Min; Ahmed, Saeed; St-Hilaire, Marc; Kim, Junsu

doi:10.3390/app11052362

Open AccessArticle

A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks

by

Muhammad Sajjad Khan

¹

,

Mohammad Faisal

²

,

Su Min Kim

¹

,

Saeed Ahmed

³

,

Marc St-Hilaire

⁴ and

Junsu Kim

^1,*

¹

Department of Electronics Engineering, Korea Polytechnic University, Gyeounggi-do 15073, Korea

²

Department of Computer Science, University of Malakand, Chakdara 18800, Pakistan

³

Department of Electrical Engineering, Mirpur University of Science and Technology, Mirpur 10250, Pakistan

⁴

Department of System and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada

^*

Author to whom correspondence should be addressed.

Appl. Sci. 2021, 11(5), 2362; https://doi.org/10.3390/app11052362

Submission received: 23 December 2020 / Revised: 27 February 2021 / Accepted: 2 March 2021 / Published: 7 March 2021

(This article belongs to the Special Issue Recent Advances on Intelligent Cognitive Radio and Dynamic Spectrum Access Techniques)

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Abstract

Cooperative spectrum sensing (CSS) is a vital part of cognitive radio networks, which ensures the existence of the primary user (PU) in the network. However, the presence of malicious users (MUs) highly degrades the performance of the system. In the proposed scheme, each secondary user (SU) reports to the fusion center (FC) with a hard decision of the sensing energy to indicate the existence of the PU. The main contribution of this work deals with MU attacks, specifically spectrum sensing data falsification (SSDF) attacks. In this paper, we propose a correlation-based approach to differentiate between the SUs and the outliers by determining the sensing of each SU, and the average value of sensing information with other SUs, to predict the SSDF attack in the system. The FC determines the abnormality of a SU by determining the similarity for each SU with the remaining SUs by following the proposed scheme and declares the SU as an outlier using the box-whisker plot. The effectiveness of the proposed scheme was demonstrated through simulations.

Keywords: cognitive radio networks; spectrum sensing data falsification (SSDF); opposite malicious user (OMU); random opposite malicious user (ROMU); box-whisker plot

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MDPI and ACS Style

Khan, M.S.; Faisal, M.; Kim, S.M.; Ahmed, S.; St-Hilaire, M.; Kim, J. A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks. Appl. Sci. 2021, 11, 2362. https://doi.org/10.3390/app11052362

AMA Style

Khan MS, Faisal M, Kim SM, Ahmed S, St-Hilaire M, Kim J. A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks. Applied Sciences. 2021; 11(5):2362. https://doi.org/10.3390/app11052362

Chicago/Turabian Style

Khan, Muhammad Sajjad, Mohammad Faisal, Su Min Kim, Saeed Ahmed, Marc St-Hilaire, and Junsu Kim. 2021. "A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks" Applied Sciences 11, no. 5: 2362. https://doi.org/10.3390/app11052362

APA Style

Khan, M. S., Faisal, M., Kim, S. M., Ahmed, S., St-Hilaire, M., & Kim, J. (2021). A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks. Applied Sciences, 11(5), 2362. https://doi.org/10.3390/app11052362

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A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks

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