Discrimination of primary user emulation attack on cognitive radio networks using machine learning based spectrum sensing scheme

IF 2.1 4区计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Wireless Networks Pub Date : 2024-04-01 DOI:10.1007/s11276-024-03720-6

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Abstract

The identification of the presence of primary user enhances the spectrum efficiency in cognitive radio (CR). The studies suggested that the existence of malicious user adversely affects the system performances; especially the primary user emulation attack (PUEA) has a greater influence in spectrum sensing on the CR network. Moreover, the detection of PUEA is a challenging and complex task and involves constructive design with sensing algorithm. In this study, a support vector machine (SVM) along with energy vectors is designed to improve the spectrum sensing mechanism. The presented approach integrates the SVM with the Bayesian optimization algorithm (BOA) in which SVM aims to detect the malicious user by randomly selecting the primary and secondary users. The BOA aims to optimize the hyperparameters of the SVM, thereby improving the detection performances and maximizes the algorithms convergence speed. The experimental analysis illustrate that the presented approach predicts the PUEA with 98% accuracy and reduces the average node power is 9.7. Moreover, the results demonstrated that the system performance does not vary on implementing it with the large-scale CR network. Finally, the system performances are compared and evaluated with existing techniques in terms of accuracy, and average noise power.

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利用基于机器学习的频谱感知方案识别认知无线电网络中的主用户仿真攻击

摘要识别主用户的存在可提高认知无线电（CR）的频谱效率。研究表明，恶意用户的存在会对系统性能产生不利影响，尤其是主用户仿真攻击（PUEA）对认知无线电网络的频谱感知影响更大。此外，PUEA 的检测是一项具有挑战性的复杂任务，涉及传感算法的建设性设计。本研究设计了支持向量机（SVM）和能量向量，以改进频谱感知机制。该方法将 SVM 与贝叶斯优化算法 (BOA) 相结合，其中 SVM 的目的是通过随机选择主用户和次用户来检测恶意用户。贝叶斯优化算法旨在优化 SVM 的超参数，从而提高检测性能，并最大限度地提高算法的收敛速度。实验分析表明，该方法预测 PUEA 的准确率为 98%，平均节点功率降低了 9.7。此外，实验结果表明，在大规模 CR 网络中实施该方法时，系统性能没有变化。最后，在准确性和平均噪声功率方面，系统性能与现有技术进行了比较和评估。

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来源期刊

Wireless Networks 工程技术-电信学

CiteScore

7.70

自引率

3.30%

发文量

314

审稿时长

5.5 months

期刊介绍： The wireless communication revolution is bringing fundamental changes to data networking, telecommunication, and is making integrated networks a reality. By freeing the user from the cord, personal communications networks, wireless LAN''s, mobile radio networks and cellular systems, harbor the promise of fully distributed mobile computing and communications, any time, anywhere. Focusing on the networking and user aspects of the field, Wireless Networks provides a global forum for archival value contributions documenting these fast growing areas of interest. The journal publishes refereed articles dealing with research, experience and management issues of wireless networks. Its aim is to allow the reader to benefit from experience, problems and solutions described.