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To mitigate primary user emulation attack trajectory using cognitive single carrier frequency division multiple access approaches: Towards next generation green IoT.
- Source :
- Engineering Reports; Dec2023, Vol. 5 Issue 12, p1-23, 23p
- Publication Year :
- 2023
-
Abstract
- The growing cognizance of spectrum scarcity has become a more significant concern in wireless radio communications. Due to the exponential growth of data transmission in intelligent wireless sensor networks, energy spectrum detection has become a promising solution for resolving spectrum shortages. Primary user emulation attack (PUEA) has been identified as a significant attack vector in the cognitive radio (CR) domain's physical layer. In comparison, the CR is a promising method to increase spectrum efficiency by allowing unlicensed secondary users (SUs) to access licensed frequency bands without interfering with approved primary users (PUs). The study's primary findings are the methodology for preventing PUEA using authentication tags, which are unique sequences. This research blends SC‐FDMA with CR to protect CR networks from PUEA attacks, a Latin square (LS) matrix tag generation system is proposed to mitigate the PUEA effect. The technology is meant to provide effective authentication and protection against malicious users. In a secured environment, the LS tag technique is utilized to track and estimate the PU. For example, the BER of both techniques is virtually identical between 0 and 4 dB, while the BER performance of the suggested LS tag generation improves with increasing signal‐to‐noise ratio (SNR). As a result, the suggested LS tag generation is less susceptible to PUEA. To diminish the influence of PUEA in CR networks, an efficient enlightening approach for making the future Green Cognitive Radio Wireless networks structure is proposed. The simulation results also demonstrate the resilience of the proposed CR spectrum sensing techniques for energy‐efficient knowledge at varying degrees to reduce the adverse effects of environmental technologies. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 25778196
- Volume :
- 5
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- Engineering Reports
- Publication Type :
- Academic Journal
- Accession number :
- 173974464
- Full Text :
- https://doi.org/10.1002/eng2.12672