Skip to main content

Advertisement

SpringerLink
Log in

Secure and efficient cooperative spectrum sensing under byzantine attack and imperfect reporting channel

  • Original Paper
  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

Cooperative spectrum sensing (CSS) has been considered as an essential paradigm of cognitive radio (CR) to provide ever-growing wireless applications with the available spectrum band. However, the following problems degrade the security and efficiency of CSS in cognitive radio networks (CRNs), such as, (i) the open facet of the CRN provides an opportunity for the Byzantine attacker to falsify the sensing information, (ii) imperfect reporting channels may distort the sensing information during the decision-making process, (iii) a large amount of sensing information transmission incurs communication overhead. Confronting these problems, we propose a secure and efficient CSS scheme, called generalized voting-sequential and differential reporting (GV-SDR) in this paper. For this aim, we first design a data transmission monitoring process in the periodic spectrum sensing frame structure to defend against Byzantine attack. Furthermore, we exploit the on/off signaling characteristic and propose a single signaling transmission method to mitigate the negative impact of the imperfect reporting channel. Moreover, based on the generalized voting (GV) rule, the sensing information fusion is carried out in the sequential and differential reporting (SDR) mechanism to improve the spectrum sensing efficiency. Simulation results show that in front of Byzantine attack and imperfect reporting channels, the proposed GV-SDR not only significantly reduces the sensing information required by the FC, but also provides the better detection performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

References

  1. Ahmad, W. S. H. M. W., Radzi, N. A. M., Samidi, F. S., Ismail, A., Abdullah, F., Jamaludin, M. Z., & Zakaria, M. N. (2020). 5G technology: Towards dynamic spectrum sharing using cognitive radio networks. IEEE Access, 8, 14460–14488.

    Article  Google Scholar 

  2. Kakkavas, G., Tsitseklis, K., Karyotis, V., & Papavassiliou, S. (2020). A software defined radio cross-layer resource allocation approach for cognitive radio networks: From theory to practice. IEEE Transactions on Cognitive Communications and Networking, 6(2), 740–755.

    Article  Google Scholar 

  3. Vaezi, A. (2020). "Cognitive radio networks: An information theoretic perspective". arXiv preprint arXiv:2001.09261.

  4. Zhao, Y., Zhou, B., Saad, W., & Luo, X. (2019). Age of information analysis for dynamic spectrum sharing. In IEEE Global Conference on Signal and Information Processing (GlobalSIP) (pp. 1–5). https://doi.org/10.1109/GlobalSIP45357.2019.8969400.

  5. Salahdine, F., & Kaabouch, N. (2020). Security threats, detection, and countermeasures for physical layer in cognitive radio networks: A survey. Physical Communication, 39, 101001.

    Article  Google Scholar 

  6. Ghorbel, M. B., Nam, H., & Alouini, M. S. (2013). Exact performance of cooperative spectrum sensing for cognitive radios with quantized information under imperfect reporting channels. In IEEE 78th Vehicular Technology Conference (VTC Fall) (pp. 1–5).

  7. Ghorbel, M. B., Nam, H., & Alouini, M. S. (2014). Soft cooperative spectrum sensing performance under imperfect and non identical reporting channels. IEEE Communications Letters, 19(2), 227–230.

    Article  Google Scholar 

  8. Wu, X., Zhang, L., & Wu, Z. (2020). Quantized soft-decision-based compressive reporting design for underlay/overlay cooperative cognitive radio networks. IEEE Transactions on Cognitive Communications and Networking, 6(3), 1044–1055.

    Article  Google Scholar 

  9. Chaudhari, S., Lunden, J., Koivunen, V., & Poor, H. V. (2012). Cooperative sensing with imperfect reporting channels: Hard decisions or soft decisions? IEEE Transactions on Signal Processing, 60(1), 18–28.

    Article  MathSciNet  Google Scholar 

  10. de Souza, R. A., dos Santos Costa, L., & de Almeida, E. M. (2019). A novel decision fusion periodogram-based algorithm for centralized cooperative spectrum sensing under errors at the report channel. In 13th European Conference on Antennas and Propagation (EuCAP). Krakow, Poland (pp. 1–5).

  11. dos Santos Costa, L., de Souza, R. A. (2020). Performance-traffic-trade-off of two novel hard decision and two soft decision fusion periodogram-based algorithms for cooperative spectrum sensing under unreliable reporting channel. IET Microwaves, Antennas & Propagation, 14(14), 1683–1695.

  12. Lee, J. W. (2013). Cooperative spectrum sensing scheme over imperfect feedback channels. IEEE Communications Letters, 17(6), 1192–1195.

    Article  Google Scholar 

  13. Zhao, J., Liu, Q., Wang, X., & Mao, S. (2018). Scheduling of collaborative sequential compressed sensing over wide spectrum band. IEEE/ACM Transactions on Networking, 26(1), 492–505.

    Article  Google Scholar 

  14. Alkheir, A. A., Mouftah, H. T. (2015). "Sequential hard-decision fusion for agile cooperative spectrum sensing". In IEEE International Conference on Communication Workshop (ICCW) (pp. 1014–1019).

  15. Bae, S., Kim, H. (2017) "ON/OFF reporting mechanism for robust cooperative sensing in cognitive IoT networks". In IEEE Wireless Communications and Networking Conference (WCNC). San Francisco (pp. 1–6).

  16. Bae, S., & Kim, H. (2016). Robust cooperative sensing with on/off signaling over imperfect reporting channels. IEEE Transactions on Industrial Informatics, 12(6), 2196–2205.

    Article  Google Scholar 

  17. Firouzabadi, A. D., & Rabiei, A. M. (2015). Sensing-throughput optimisation for multichannel cooperative spectrum sensing with imperfect reporting channels. IET Communications, 9(18), 2188–2196.

    Article  Google Scholar 

  18. Li, M., Alhussein, O., Sofotasios, P. C., Muhaidat, S., Yoo, P. D., Liang, J., Wang, A. (2019). Censor-based multi-antenna cooperative spectrum sensing over erroneous feedback channels. In IEEE Wireless Communications and Networking Conference (WCNC). Marrakesh, Morocco (pp. 1–6).

  19. Li, M., Alhussein, O., Sofotasios, P. C., Muhaidat, S., Yoo, P. D., Liang, J., & Wang, A. (2020). Censor-based cooperative multi-antenna spectrum sensing with imperfect reporting channels. IEEE Transactions on Sustainable Computing, 5(1), 48–60.

    Article  Google Scholar 

  20. Naderipour, M., Taherpour, A., Taherpour, A., & Gazor, S. (2020). Design of optimal non-uniform quantizer in imperfect noisy reporting channels for collaborative spectrum sensing. IEEE Transactions on Vehicular Technology, 69(11), 12870–12882.

    Article  Google Scholar 

  21. Kumar, A., Pandit, S., & Singh, G. (2020). Optimisation of censoring-based cooperative spectrum sensing approach with multiple antennas and imperfect reporting channel scenarios for cognitive radio network. IET Communications, 14(16), 2666–2676.

    Article  Google Scholar 

  22. Kumar, A., Pandit, S., & Singh, G. (2020). Threshold selection analysis of spectrum sensing for cognitive radio network with censoring based imperfect reporting channels. Wireless Networks. https://doi.org/10.1007/s11276-020-02488-9

    Article  Google Scholar 

  23. Ma, L., Xiang, Y., Pei, Q., Xiang, Y., & Zhu, H. (2017). Robust reputation-based cooperative spectrum sensing via imperfect common control channel. IEEE Transactions on Vehicular Technology, 67(5), 3950–3963.

    Article  Google Scholar 

  24. Yilmaz, H. B., Tugcu, T., & Alagoz, F. (2014). Novel quantization-based spectrum sensing scheme under imperfect reporting channel and false reports. International Journal of Communication Systems, 27(10), 1459–1475.

    Article  Google Scholar 

  25. Ahmed, A. T., López-Beníte, M., Selis, V., Patel, D. K., & Umebayashi, K. (2018). Cooperative estimation of primary traffic under imperfect spectrum sensing and Byzantine attacks. IEEE Access, 6, 61651–61664.

    Article  Google Scholar 

  26. Fu, Y., & He, Z. (2019). Entropy-based weighted decision combining for collaborative spectrum sensing over Byzantine attack. IEEE Wireless Communications Letters, 8(6), 1528–1532.

    Article  Google Scholar 

  27. Wu, J., Song, T., Wang, C., Hu, J. (2018). "Reputation value ranking based sequential cooperative spectrum sensing against Byzantine attack". In IEEE International Conference on Communications Workshops (ICC Workshops). Kansas City, MO (pp. 1–6).

  28. Jun, W., Tiecheng, S., Yue, Y., Cong, W., & Jing, H. (2018). Sequential cooperative spectrum sensing in the presence of dynamic byzantine attack for mobile networks. PLoS ONE, 13(7), e0199546.

    Article  Google Scholar 

  29. Wu, J., Song, T., Yu, Y., Wang, C., & Hu, J. (2019). Reuse of byzantine data in cooperative spectrum sensing using sequential detection. IET Communications, 14(2), 251–261.

    Article  Google Scholar 

  30. Wu, J., Yu, Y., Song, T., & Hu, J. (2019). Sequential 0/1 for cooperative spectrum sensing in the presence of strategic Byzantine attack. IEEE Wireless Communications Letters, 8(2), 500–503.

    Article  Google Scholar 

  31. Wu, J., Song, T., Wang, C., Yu, Y., Liu, M., Hu, J. (2017). Robust cooperative spectrum sensing against probabilistic SSDF attack in cognitive radio networks. In IEEE 86th Vehicular Technology Conference (VTC-Fall). Toronto, ON (pp. 1–6).

  32. Wu, J., Yu, Y., Zhu, H., Song, T., & Hu, J. (2020). Cost-benefit tradeoff of Byzantine attack in cooperative spectrum sensing. IEEE Systems Journal, 14(2), 2532–2543.

    Article  Google Scholar 

  33. Wu, J., Li, P., Chen, Y., Tang, J., Wei, C., Xia, L., & Song, T. (2020). Analysis of Byzantine attack strategy for cooperative spectrum sensing. IEEE Communications Letters, 24(8), 1631–1635.

    Article  Google Scholar 

  34. Lo, B. F. (2011). A survey of common control channel design in cognitive radio networks. Physical Communication, 4(1), 26–39.

    Article  Google Scholar 

  35. Luan, H., Li, O., Zhang, X. (2014). "Cooperative spectrum sensing with energy-efficient sequential decision fusion rule". In IEEE 23rd Wireless and Optical Communication Conference (WOCC) (pp. 1–4).

  36. Wu, J., Song, T., Yu, Y., Wang, C., & Hu, J. (2018). Generalized Byzantine attack and defense in cooperative spectrum sensing for cognitive radio networks. IEEE Access, 6, 53272–53286.

    Article  Google Scholar 

  37. Chen, R., Park, J. M. J., & Bian, K. (2012). Robustness against Byzantine failures in distributed spectrum sensing. Computer Communications, 35(17), 2115–2124.

    Article  Google Scholar 

  38. Varshney, P. K. (2012). Distributed detection and data fusion. Springer Science & Business Media.

Download references

Funding

Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (No. 2022D16), Fundamental Research Funds for the Provincial Universities of Zhejiang (No. GK209907299001-023), Open Fund Project of Sichuan Provincial Key Laboratory of Artificial Intelligence (No. 2021RYJ07), and 2020 Annual Teachers' Professional Development Project of Domestical Visiting Scholars in Institutions of Higher Education (No. FX2020009).

Author information

Authors and Affiliations

  1. School of Communication Engineering, Hangzhou Dianzi University, Jianggan District, Hangzhou, Zhejiang Province, China

    Jun Wu & Zehao Chen

  2. National Mobile Communications Research Laboratory, Southeast University, Nanjing, Jiangsu Province, China

    Jun Wu & Zehao Chen

  3. Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Yibin, Sichuan Province, China

    Jun Wu

  4. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, Zhejiang Province, China

    Jun Wu

Authors
  1. Jun Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zehao Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jun Wu.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wu, J., Chen, Z. Secure and efficient cooperative spectrum sensing under byzantine attack and imperfect reporting channel. Wireless Netw 28, 367–380 (2022). https://doi.org/10.1007/s11276-021-02853-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-021-02853-2

Keywords

Search

Navigation