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

被引：4

作者：

Chouhan, Ankit ^{[1
]}

Parmar, Ashok ^{[1
]}

Captain, Kamal ^{[1
]}

Lopez-Benitez, Miguel ^{[2
,3
]}

机构：

[1] Sardar Vallabhbhai Natl Inst Technol, Dept Elect & Commun Engn, Surat 395007, India

[2] Univ Liverpool, Dept Elect Engn & Elect, Liverpool L69 3GJ, England

[3] Antonio de Nebrija Univ, ARIES Res Ctr, Madrid 28248, Spain

来源：

IEEE WIRELESS COMMUNICATIONS LETTERS | 2024年 / 13卷 / 05期

关键词：

Cooperative spectrum sensing; cognitive radio network; Byzantine attack; machine learning; principal component analysis;

D O I：

10.1109/LWC.2024.3377275

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：1488 / 1492

页数：5

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