KSII Transactions on Internet and Information Systems (TIIS)

Korean Society for Internet Information (한국인터넷정보학회)
권호 표지
DOI QR코드

DOI QR Code

Attack-Proof Cooperative Spectrum Sensing Based on Consensus Algorithm in Cognitive Radio Networks

  • Liu, Quan (Department of Communication Engineering, Naval University of Engineering) ;
  • Gao, Jun (Department of Communication Engineering, Naval University of Engineering) ;
  • Guo, Yunwei (Department of Communication Engineering, Naval University of Engineering) ;
  • Liu, Siyang (Department of Communication Engineering, Naval University of Engineering)
  • Received : 2010.07.25
  • Accepted : 2010.10.17
  • Published : 2010.12.23
Download PDF
⟨ Previous Next ⟩

Abstract

Cooperative spectrum sensing (CSS) is an effective technology for alleviating the unreliability of local spectrum sensing due to fading/shadowing effects. Unlike most existing solutions, this paper considers the use of CSS technology in decentralized networks where a fusion center is not available. In such a decentralized network, some attackers may sneak into the ranks of cooperative users. On the basis of recent advances in bio-inspired consensus algorithms, an attack-proof, decentralized CSS scheme is proposed in which all secondary users can maintain cooperative sensing by exchanging information locally instead of requiring centralized control or data fusion. Users no longer need any prior knowledge of the network. To counter three potential categories of spectrum sensing data falsification (SSDF) attacks, some anti-attack strategies are applied to the iterative process of information exchange. This enables most authentic users to exclude potentially malicious users from their neighborhood. As represented by simulation results, the proposed scheme can generally ensure that most authentic users reach a consensus within the given number of iterations, and it also demonstrates much better robustness against different SSDF attacks than several existing schemes.

Keywords

References

  1. FCC, "ET Docket No. 03-222, Notice of proposed rulemaking and order," Federal Communications Commission, Washington, D.C., 2003.
  2. Q. Liu, J. Gao, J. Guan and Y. Guo, "A survey on linker layer key technologies in cognitive radio networks (in Chinese)," Telecommunication Engineering, vol. 50, no. 3, pp. 90-98, 2010.
  3. H. Urkowitz, "Energy detection of unknown deterministic signals," in Proc. of IEEE, vol. 55, no. 4, pp. 523-531, 1967. https://doi.org/10.1109/PROC.1967.5573
  4. F. F. Digham, M. Alouini and M. K. Simon, "On the energy detection of unknown signals over fading channels," in Proc. of IEEE International Conf. on Communications, Alaska, USA, pp. 3575-3579, 2003.
  5. A. Ghasemi and E. S. Sousa, "Opportunistic spectrum access in fading channels through collaborative sensing," Journal of Communications (JCM), vol. 2, no. 2, pp. 71-82, 2007.
  6. B. Shen, S. Ullah and K. Kwak, "Deflection coefficient maximization criterion based optimal cooperative spectrum sensing," AEU - International Journal of Electronics and Communications, vol. 64, no. 9, pp. 819-827, 2010. https://doi.org/10.1016/j.aeue.2009.06.006
  7. B. Shen and K. S. Kwak, "Soft combination schemes for cooperative spectrum sensing in cognitive radio networks," ETRI Journal, vol. 31, no. 3, pp. 263-270, 2009. https://doi.org/10.4218/etrij.09.0108.0501
  8. J. Ma and Y. Li, "Soft combination and detection for cooperative spectrum sensing in cognitive radio networks," in Proc. of IEEE Global Telecommunications Conf., GLOBECOM, Washington, DC, USA, pp. 3139-3143, 2007.
  9. J. Shen, S. Liu, L. Zeng, G. Xie, J. Gao and Y. Liu, "Optimisation of cooperative spectrum sensing in cognitive radio network," IET Communications, vol. 3, no. 7, pp. 1170-1178, 2009. https://doi.org/10.1049/iet-com.2008.0177
  10. D. Oh and Y. Lee, "Cooperative spectrum sensing with imperfect feedback channel in the cognitive radio systems," International Journal of Communication Systems, vol. 23, no. 3, pp. 763-779, 2010.
  11. G. Ganesan and Y. Li, "Cooperative spectrum sensing in cognitive radio, Part II: multiuser networks," IEEE Transactions on Wireless Communications, vol. 6, no. 6, pp. 2214-2222, 2007. https://doi.org/10.1109/TWC.2007.05776
  12. Z. Li, F. R. Yu and M. Huang, "A cooperative spectrum sensing consensus scheme in cognitive radios," in Proc. of IEEE Communications Society Conference on Computer Communications, Leblon, Brazil, pp. 2546-2550, 2009.
  13. F. R. Yu, M. Huang and H. Tang, "Biologically inspired consensus-based spectrum sensing in mobile ad Hoc networks with cognitive radios," IEEE Networks, no. May/June, pp. 26-30, 2010.
  14. R. Chen, J. Park, Y. T. Hou and J. H. Reed, "Toward secure distributed spectrum sensing in cognitive radio networks," IEEE Communications Magazine, vol. 46, no. 4, pp. 50-55, 2008.
  15. R. Chen, J. Park and J. H. Reed, "Defense against primary user emulation attacks in Cognitive Radio networks," IEEE Journal on Selected Areas in Communications, vol. 26, no. 1, pp. 25-37, 2008. https://doi.org/10.1109/JSAC.2008.080104
  16. R. Chen, J. Park and K. Bian, "Robust distributed spectrum sensing in cognitive radio networks," in Proc. of IEEE Communications Society Conf. on Computer Communications, Phoenix, AZ, USA, pp. 31-35, 2008.
  17. H. Li and Z. Han, "Catching attacker(s): for collaborative spectrum sensing in cognitive radio systems: an abnormality detection approach," in Proc. of IEEE Symposium on New Frontiers in Dynamic Spectrum, Singapore, pp. 1-12, 2010.
  18. F. R. Yu, H. Tang, M. Huang, Z. Li and P. C. Mason, "Defense against spectrum sensing data falsification attacks in mobile ad hoc networks with cognitive radios," in Proc. of IEEE Military Communications Conf., MILCOM, Boston, MA, USA, pp. 1-7, 2009.
  19. R. Olfati-Saber, J. A. Fax and R. M. Murray, "Consensus and cooperation in networked multi-agent systems," in Proc. Proc. of the IEEE, vol. 95, no. 1, pp. 215-233, 2007. https://doi.org/10.1109/JPROC.2006.887293
  20. A. Ghasemi and E. S. Sousa, "Optimization of spectrum sensing for opportunistic spectrum access in cognitive radio networks," in Proc. of 4th Annual IEEE Consumer Communications and Networking Conference, Las Vegas, NV, USA, pp. 1022-1026, 2007.
  21. A. Ghasemi and E. S. Sousa, "Spectrum sensing in cognitive radio networks: requirements, challenges and design trade-offs," IEEE Communications Magazine, vol. 46, no., 4 pp. 32-39, 2008.
  22. H. Kim and K. G. Shin, "Efficient discovery of spectrum opportunities with MAC-layer sensing in cognitive radio networks," IEEE Transactions on Mobile Computing, vol. 7, no. 5, pp. 533-545, 2008. https://doi.org/10.1109/TMC.2007.70751
  23. X. Lin, S. Boyd and S. Lall, "A scheme for robust distributed sensor fusion based on average consensus," in Proc. of 4th International Symposium on Information Processing in Sensor Networks, IPSN, Los Angeles, USA, pp. 63-70, 2005.
  24. W. Ren and R. W. Beard, "Consensus seeking in multiagent systems under dynamically changing interaction topologies," IEEE Transactions on Automatic Control, pp. 655-661, 2005.
  25. A. Jadbabaie, J. Lin and A. S. Morse, "Coordination of groups of mobile autonomous agents using nearest neighbor rules," IEEE Transactions on Automatic Control, vol. 48,no. 6, pp. 988-1001, 2003. https://doi.org/10.1109/TAC.2003.812781
  26. J. G. Proakis, "Digital Communications (Fourth Edition)," New York: MCGraw-Hill, 2001.
  27. M. Abramowitz and I. A. Stegun, "Handbook of Mathematical Functions, National Bureau of Standards, Applied Math. Series #55," New York: Dover Publications, 1965.
  28. S. Kyperountas, N. Correal, Q. Shi and Z. Ye, "Performance analysis of cooperative spectrum sensing in suzuki fading channels," in Proc. of 2nd International Conf. on Cognitive Radio Oriented Wireless Networks and Communications, CrownCom, Orlando, USA, pp. 428-432, 2007.

Cited by

  1. Analysis and Optimization of Cooperative Spectrum Sensing with Noisy Decision Transmission vol.5, pp.4, 2010, https://doi.org/10.3837/tiis.2011.04.002
  2. Entropy-based Spectrum Sensing for Cognitive Radio Networks in the Presence of an Unauthorized Signal vol.9, pp.1, 2015, https://doi.org/10.3837/tiis.2015.01.002