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CDCSS: cluster-based distributed cooperative spectrum sensing model against primary user emulation (PUE) cyber attacks

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Abstract

In cognitive radio network, the secondary users (SUs) use the spectrum of primary users for communication which arises the security issues. The status of SUs as legitimate users is compulsory for the stability of the system. This paper addresses the issue of delay caused by a band-selection decision process that directly affects the security and performance. The model cluster-based distributed cooperative spectrum sensing is proposed. In this model, cluster heads (CHs) exchange control information with other CHs and ordinary nodes. This model significantly reduced the delay, sensing, convergence, routing, in band-selection process. This also reduces the energy consumption while sensing the spectrum which seriously leads to performance upgradation. The simulated results show the improved performance of cognitive radio networks in terms of delay, packet loss ratio and bandwidth usage as compared to cluster-based cooperative spectrum sensing model. The opportunity for primary user emulation attacker is minimized as the overall delay is reduced.

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Author information

Authors and Affiliations

  1. Department of Computer Science, National Textile University, Faisalabad, Pakistan

    Muhammad Ayzed Mirza, Mudassar Ahmad, Muhammad Asif Habib, Nasir Mahmood & C. M. Nadeem Faisal

  2. Department of Computer Science, Lahore College for Women University, Lahore, Pakistan

    Usman Ahmad

  3. Human Communication and Interaction Research Group, Department of Computing, University of Oviedo, Oviedo, Spain

    C. M. Nadeem Faisal

Authors
  1. Muhammad Ayzed Mirza

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  2. Mudassar Ahmad

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  3. Muhammad Asif Habib

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  4. Nasir Mahmood

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  5. C. M. Nadeem Faisal

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  6. Usman Ahmad

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Corresponding author

Correspondence toMuhammad Asif Habib.

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Mirza, M.A., Ahmad, M., Habib, M.A.et al. CDCSS: cluster-based distributed cooperative spectrum sensing model against primary user emulation (PUE) cyber attacks.J Supercomput74, 5082–5098 (2018). https://doi.org/10.1007/s11227-018-2378-6

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