Skip to main content
SpringerLink
Log in

Dynamic Spectrum Utilization with Secure Sensing in E-Healthcare System

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

To enhance the quality of medical care, e-healthcare system becomes a promising system which integrates diverse wireless devices and technologies such as internet of things, wireless body area networks, etc. However, numerous wireless devices and communication requirements will cause the shortage of the wireless spectrum. Cognitive radio is able to exploit spectrum opportunities and increase the communication performance for the e-healthcare system. To access the spectrum safely, the security aspect of spectrum utilization should be carefully addressed. A well-known threat to the spectrum utilization is the primary user emulation attack (PUEA) in which the attackers emulate as the primary users to obtain spectrum opportunities. To defend this threat, in this paper, we propose a triple threshold energy detection (TTED) to identify the PUEA. Based on the TTED, legitimate devices are allowed to access the available channels when the licensed channel is idle or occupied by attackers. To evaluate our proposed access scheme, we derive the achievable throughput while the average transmission time is fixed and exponential distributed, respectively.

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

Similar content being viewed by others

References

  1. Lee, H., Park, K.-J., Ko, Y., & Choi, C.-H. (2011). Wireless LAN with medical-grade QoS for e-healthcare. Journal of Communications and Networks, 13(2), 13–18.

    Google Scholar 

  2. Ferrer-Roca, O., Marcano, F., & Diaz-Cardama, A. (2008). Quality labels for e-health. IET Communications, 2(2), 202–207.

    Article  Google Scholar 

  3. Yan, H., Huo, H., Xu, Y., & Gi dlund, M. (2010). Wireless sensor network based E-health system: Implementation and experimental results. IEEE Transactions on Consumer Electronics, 56(4), 2288–2295.

    Article  Google Scholar 

  4. Phunchongharn, P., Niyato, D., Hossain, E., & Camorlinga, S. (2010). An EMI-aware prioritized wireless access scheme for e-health applications in hospital environments. IEEE Transactions on Information Technology in Biomedicine, 14(5), 1247–1258.

    Article  Google Scholar 

  5. Yuan, X., Wang, X., Wang, C., Weng, J., & Ren, K. (2016). Enabling secure and fast indexing for privacy-assured healthcare monitoring via compressive sensing. IEEE Transactions on Multimedia, 18(10), 2002–2014.

    Article  Google Scholar 

  6. Yang, Y., Xu, Z., Liu, L., et al. (2017). A security carving approach for AVI video based on frame size and index. Multimed Tools Appl, 76(3), 3293–3312.

    Article  Google Scholar 

  7. Zhou, G., Cichocki, A., Zhang, Y., & Mandic, D. (2016). Group component analysis from multi-block data: Common and individual feature extraction. IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/TNNLS.2015.2487364.

    Google Scholar 

  8. Yang, Z., Xiang, Y., Xie, K., & Lai, Y. (2016). Adaptive method for nonsmooth nonnegative matrix factorization. IEEE Transactions on Neural Networks and Learning Systems. doi:10.1109/TNNLS.2016.2517096.

    Google Scholar 

  9. Ye, J., Xu, Z., et al. (2016). Secure outsourcing of modular exponentiations under single untrusted programme model. Journal of Computer and System Sciences. doi:10.1016/j.jcss.2016.11.005.

    Google Scholar 

  10. Mitola, J., & Maguire, G. Q. (1999). Cognitive radios: Making software radios more personal. IEEE Personal Communications, 6(4), 13–18.

    Article  Google Scholar 

  11. Liu, Y., Pan, M., Yu, R., Zhang, Y., & Xie, S. (2017). SD-MAC: Spectrum database-driven MAC protocol for cognitive machine-to-machine networks. IEEE Transactions on Vehicular Technology, 66, 1456–1467.

    Article  Google Scholar 

  12. Liu, Y., Yang, Z., Yu, R., Xiang, Y., & Xie, S. (2015). An efficient MAC protocol with adaptive energy harvesting for machine-to-machine networks. IEEE ACCESS, 3, 358–367.

    Article  Google Scholar 

  13. J. Mitola (2000). Cognitive radio: An integrated agent architecture for software defined radio. Ph.D. Thesis, KTH Royal Inst. Technology, Stockholm, Sweden.

  14. Yu, R., Zhong, W., Xie, S., & Zhang, Y. (2016). QoS differential scheduling in cognitive-radio-based smart grid networks: An adaptive dynamic programming approach. IEEE Transactions on Neural Networks and Learning Systems, 27(2), 435–443.

    Article  MathSciNet  Google Scholar 

  15. Chen, R., Park, J. M., Hou, Y. T., & Reed, J. H. (2008). Toward secure distributed spectrum sensing in cognitive radio networks. IEEE Communications Magazine, 46(4), 50–55.

    Article  Google Scholar 

  16. Chen, R., & Park, J. M. (2006). Ensuring trustworthy spectrum sensing in cognitive radio networks. In Proceedings of IEEE workshop networking technologies for software defined radio networks (pp. 110–119), September 2006.

  17. Chen, R., Park, J. M., & Reed, J. H. (2008). Defense against primary user emulation attacks in cognitive radio networks. IEEE Journal on Selected Areas in Communications, 26(1), 25–37.

    Article  Google Scholar 

  18. Anand, S., Jin, Z., & Subbalakshmi, K. P. (2008). An analytical model for primary user emulation attacks in cognitive radio networks. In Proceedings of IEEE DYSPAN, 1–6 October 2008.

  19. Liu, Y., Yu, R., Zhang, Y., & Xie, S.-L. (2010). A group-based cooperative medium access control protocol for cognitive radio networks. In Proceedings of IWQOS, 1–9 June 2010.

  20. Liu, Y., Xie, S. L., Yu, R., & Zhang, Y. (2013). An efficient MAC protocol with selective grouping and cooperative sensing in cognitive radio networks. IEEE Transactions on Vehicular Technology, 62(8), 3928–3941.

    Article  Google Scholar 

  21. Liu, Y., Xie, S. L., Yu, R., & Zhang, Y. (2015). Exploiting temporal and spatial diversities for opportunistic spectrum access in cognitive vehicular networks. Wiley Wireless Communications and Mobile Computing (WCMC), 15(17), 2079–2094.

    Article  Google Scholar 

  22. Shiang, H.-P., & Schaar, M. (2008). Queuing-based dynamic channel selection for heterogeneous multimedia applications over cognitive radio networks. IEEE Transactions on Multimedia, 10(5), 896–909.

    Article  Google Scholar 

  23. Cabric, D., Mishra, S. M., & Brodersen, R. W. (2004). Implementation issues in spectrum sensing for cognitive radios. In Proceedings of Asilomar conference on signals, systems, and computers.

  24. Liu, Y., Yuen, C., Yu, R., Zhang, Y., & Xie, S. (2016). Queuing-based energy consumption management for heterogeneous residential demands in smart grid. IEEE Transactions on Smart Grid, 7(3), 1650–1659.

    Article  Google Scholar 

  25. Liu, Y., Zhang, Y., Yu, R., & Xie, S. (2015). Integrated energy and spectrum harvesting for 5G wireless communications. IEEE Network Magazine, 29(3), 75–81.

    Article  Google Scholar 

  26. Ash, R., & Ash, C. (1993). The calculus tutoring book: The derivative part I. New York, NY: Wiley.

    Book  MATH  Google Scholar 

  27. Zhou, G., Zhao, Q., Zhang, Y., Adali, T., Xie, S., et al. (2016). Linked component analysis from matrices to high-order tensors: Applications to biomedical data. Proceedings of the IEEE, 104(2), 310–331.

    Article  Google Scholar 

  28. Vinel, A., Ni, Q., Staehle, D., & Turlikov, A. (2009). Capacity analysis of reservation-based random access for broadband wireless access networks. IEEE Journal on Selected Areas in Communications, 27(2), 172–181.

    Article  Google Scholar 

  29. Hasan, M., Hossain, E., & Niyato, D. (2013). Random access for machine-to-machine communication in LTE-advanced networks: Issues and approaches. IEEE Communications Magazine, 51(6), 86–93.

    Article  Google Scholar 

  30. Saleem, K., Derhab, A., Almuhtadi, J., & Shahzad, B. (2015). Human-oriented design of secure machine-to-machine communication system for e-Healthcare society. Computers in Human Behavior, 51, 977–985.

    Article  Google Scholar 

  31. Jung, S., Myllyla, R., & Chung, W. (2013). Wireless machine-to-machine healthcare solution using android mobile devices in global networks. IEEE Sensors Journal, 13(5), 1419–1424.

    Article  Google Scholar 

  32. Egbogah, E. E., & Fapojuwo, A. O. (2011). A survey of system architecture requirements for health care-based wireless sensor networks. Sensors, 11(5), 4875–4898.

    Article  Google Scholar 

  33. Jin, W., Abid, H., Lee, S., Lei, S., & Feng, X. (2011). A secured health care application architecture for cyber-physical systems. Control Engineering and Applied Informatics, 13(3), 101–108.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Guangdong University of Technology, Guangzhou, 510006, China

    Chuan Lu, Bin Zhang & Jie Xu

Authors
  1. Chuan Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bin Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jie Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chuan Lu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lu, C., Zhang, B. & Xu, J. Dynamic Spectrum Utilization with Secure Sensing in E-Healthcare System. Wireless Pers Commun 95, 2285–2298 (2017). https://doi.org/10.1007/s11277-017-4091-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-4091-9

Keywords

Search

Navigation