Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm
Cognitive radio network (CRN) uses the available spectrum resources wisely. Spectrum sensing is the central element of a CRN. However, spectrum sensing is susceptible to multiple security breaches caused by malicious users (MUs). These attackers attempt to change the sensed result in order to decrea...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Blockchain: Research and Applications |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S209672092400037X |
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| author | Evelyn Ezhilarasi I J. Christopher Clement |
| author_facet | Evelyn Ezhilarasi I J. Christopher Clement |
| author_sort | Evelyn Ezhilarasi I |
| collection | DOAJ |
| description | Cognitive radio network (CRN) uses the available spectrum resources wisely. Spectrum sensing is the central element of a CRN. However, spectrum sensing is susceptible to multiple security breaches caused by malicious users (MUs). These attackers attempt to change the sensed result in order to decrease network performance. In our proposed approach, with the help of blockchain-based technology, the fusion center is able to detect and prevent such criminal activities. The method of our model makes use of blockchain-based MU detection with SHA-3 hashing and energy detection-based spectrum sensing. The detection strategy takes place in two stages: block updation phase and iron out phase. The simulation results of the proposed method demonstrate 3.125%, 6.5%, and 8.8% more detection probability at −5 dB signal-to-noise ratio (SNR) in the presence of MUs, when compared to other methods like equal gain combining (EGC), blockchain-based cooperative spectrum sensing (BCSS), and fault-tolerant cooperative spectrum sensing (FTCSS), respectively. Thus, the security of cognitive radio blockchain network is proved to be significantly improved. |
| format | Article |
| id | doaj-art-0aa1084b811a46c895ede5cc024a0a74 |
| institution | OA Journals |
| issn | 2666-9536 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Blockchain: Research and Applications |
| spelling | doaj-art-0aa1084b811a46c895ede5cc024a0a742025-08-20T02:30:30ZengElsevierBlockchain: Research and Applications2666-95362024-12-015410022410.1016/j.bcra.2024.100224Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithmEvelyn Ezhilarasi I0J. Christopher Clement1Department of Communication Engineering, School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, IndiaCorresponding author.; Department of Communication Engineering, School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, IndiaCognitive radio network (CRN) uses the available spectrum resources wisely. Spectrum sensing is the central element of a CRN. However, spectrum sensing is susceptible to multiple security breaches caused by malicious users (MUs). These attackers attempt to change the sensed result in order to decrease network performance. In our proposed approach, with the help of blockchain-based technology, the fusion center is able to detect and prevent such criminal activities. The method of our model makes use of blockchain-based MU detection with SHA-3 hashing and energy detection-based spectrum sensing. The detection strategy takes place in two stages: block updation phase and iron out phase. The simulation results of the proposed method demonstrate 3.125%, 6.5%, and 8.8% more detection probability at −5 dB signal-to-noise ratio (SNR) in the presence of MUs, when compared to other methods like equal gain combining (EGC), blockchain-based cooperative spectrum sensing (BCSS), and fault-tolerant cooperative spectrum sensing (FTCSS), respectively. Thus, the security of cognitive radio blockchain network is proved to be significantly improved.http://www.sciencedirect.com/science/article/pii/S209672092400037XSpectrum sensingBlockchainCognitive radio networkSHA-3Malicious users |
| spellingShingle | Evelyn Ezhilarasi I J. Christopher Clement Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm Blockchain: Research and Applications Spectrum sensing Blockchain Cognitive radio network SHA-3 Malicious users |
| title | Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm |
| title_full | Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm |
| title_fullStr | Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm |
| title_full_unstemmed | Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm |
| title_short | Robust cooperative spectrum sensing in cognitive radio blockchain network using SHA-3 algorithm |
| title_sort | robust cooperative spectrum sensing in cognitive radio blockchain network using sha 3 algorithm |
| topic | Spectrum sensing Blockchain Cognitive radio network SHA-3 Malicious users |
| url | http://www.sciencedirect.com/science/article/pii/S209672092400037X |
| work_keys_str_mv | AT evelynezhilarasii robustcooperativespectrumsensingincognitiveradioblockchainnetworkusingsha3algorithm AT jchristopherclement robustcooperativespectrumsensingincognitiveradioblockchainnetworkusingsha3algorithm |