Publication Type : Journal Article
Source : Computers and Electrical Engineering, Volume 106, 2023
Url : https://www.sciencedirect.com/science/article/pii/S0045790623000447
Keywords : Cognitive Radio Sensor Network, Primary User Emulation Attack (PUEA), Software Defined Radio, Energy efficiency, Error probability, Throughput
Campus : Coimbatore
School : School of Engineering
Department : Electronics and Communication
Verified : No
Year : 2022
Abstract : A Cognitive Radio Sensor Network (CRSN) is a promising technology incorporating cognitive radio in traditional wireless sensor networks. In general, Primary User Emulation Attack (PUEA) is becoming the major bottleneck for implementing CRSN in reality. In CRSN-PUEA, malicious users are also equipped with a Spectrum Sensing capability, the so-called smart PEUA, which further complicates the spectrum access of Cognitive Users (CU). In this paper, we propose a novel Energy-Efficient Adaptive Sensing (EEAS) technique for CRSN to overcome the spectrum access problem in the presence of PUEA. The proposed EEAS enhances the sensing accuracy by differentiating the PUEA and Primary User signals that, reduce the sensing error probability and enhance the underlying system model’s throughput and energy efficiency. The numerical results show that the proposed EEAS technique has improved the throughput and energy efficiency by about 12% and 44%, respectively, compared to the state-of-the-art works in the field of PUEA-CRSN. In addition, it is observed that the sensing error probability is reduced by 22%. Furthermore, a Software Defined Radio (SDR) based hardware system setup has been developed to verify the functionality of the proposed system model.
Cite this Research Publication : Bala Vishnu J., Saswat Kumar Ram, Deepan, Energy-efficient adaptive sensing for Cognitive Radio Sensor Network in the presence of Primary User Emulation Attack, Computers and Electrical Engineering, Volume 106, 2023, 108619, ISSN 0045-7906, https://doi.org/10.1016/j.compeleceng.2023.108619.