Version 1
: Received: 13 July 2024 / Approved: 15 July 2024 / Online: 15 July 2024 (17:10:20 CEST)
How to cite:
Wu, J.; Liu, T.; Zhao, R. Beta Distribution Function for Cooperative Spectrum Sensing Against Byzantine Attack in Cognitive Wireless Sensor Networks. Preprints2024, 2024071194. https://doi.org/10.20944/preprints202407.1194.v1
Wu, J.; Liu, T.; Zhao, R. Beta Distribution Function for Cooperative Spectrum Sensing Against Byzantine Attack in Cognitive Wireless Sensor Networks. Preprints 2024, 2024071194. https://doi.org/10.20944/preprints202407.1194.v1
Wu, J.; Liu, T.; Zhao, R. Beta Distribution Function for Cooperative Spectrum Sensing Against Byzantine Attack in Cognitive Wireless Sensor Networks. Preprints2024, 2024071194. https://doi.org/10.20944/preprints202407.1194.v1
APA Style
Wu, J., Liu, T., & Zhao, R. (2024). Beta Distribution Function for Cooperative Spectrum Sensing Against Byzantine Attack in Cognitive Wireless Sensor Networks. Preprints. https://doi.org/10.20944/preprints202407.1194.v1
Chicago/Turabian Style
Wu, J., Tianle Liu and Rui Zhao. 2024 "Beta Distribution Function for Cooperative Spectrum Sensing Against Byzantine Attack in Cognitive Wireless Sensor Networks" Preprints. https://doi.org/10.20944/preprints202407.1194.v1
Abstract
In order to explore more spectrum resources to support sensors and its related applications, cognitive wireless sensor networks (CWSNs) have emerged to identify available channels being underutilized by the primary user (PU). To improve the detection accuracy of the PU signal, cooperative spectrum sensing (CSS) among sensors paradigm is proposed to make a global decision about the PU status for CWSNs. However, CSS is susceptible to Byzantine attack from malicious sensor nodes due to its open nature, resulting in wastage of spectrum resources or causing harmful interference to PUs. To suppress the negative impact of Byzantine attack, this paper proposes a beta distribution function (BDF) for CSS among multiple sensors, which includes a sequential process, beta reputation model, and weight evaluation. Based on sequential probability ratio test (SPRT), we integrate the proposed beta reputation model into SPRT, while improving and reducing the positive and negative impacts of reliable and unreliable sensor nodes on the global decision, respectively. Finally, the numerical simulation results demonstrate that compared to SPRT and weighted sequential probability ratio test (WSPRT), the proposed BDF has outstanding effects in terms of the error probability, and average number of samples under various attack ratios and probabilities.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
