Defending Against Byzantine Attacks in CRNs: PCA-Based Malicious User Detection and Weighted Cooperative Spectrum Sensing

Chouhan, Ankit ORCID: 0000-0001-6358-3045, Parmar, Ashok ORCID: 0000-0003-1137-043X, Captain, Kamal ORCID: 0000-0003-0865-137X and López-Benítez, Miguel ORCID: 0000-0003-0526-6687 (2024) Defending Against Byzantine Attacks in CRNs: PCA-Based Malicious User Detection and Weighted Cooperative Spectrum Sensing. IEEE Wireless Communications Letters, PP (99). p. 1.

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Official URL: http://dx.doi.org/10.1109/lwc.2024.3377275

Abstract

Cognitive radio (CR) technology is a viable solution for assisting secondary users to share the licensed radio spectrum of primary users. Cooperative spectrum sensing (CSS) enhances the accuracy of spectrum sensing in a CR network. However, the effectiveness of CSS can be compromised by malicious users (MUs) who intentionally send false sensing information to the fusion center. This letter focuses on enhancing the CSS performance and detecting the MUs. We propose a machine learning technique to identify and classify MUs in a CR network using the Principal Component Analysis algorithm. The performance of the proposed algorithm in detecting MUs and enhancing CSS performance is validated through simulation experiments.

Item Type:	Article
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	11 Mar 2024 10:39
Last Modified:	02 Apr 2024 15:39
DOI:	10.1109/lwc.2024.3377275
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3179251