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Towards trustworthy collaboration in spectrum sensing for ad hoc cognitive radio networks

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Abstract

Cognitive radio networks (CRN) make use of dynamic spectrum access to communicate opportunistically in frequency bands otherwise licensed to incumbent primary users such as TV broadcast. To prevent interference to primary users it is vital for secondary users in CRNs to conduct accurate spectrum sensing, which is especially challenging when the transmission range of primary users is shorter compared to the size of the CRN. This task becomes even more challenging in the presence of malicious secondary users that launch spectrum sensing data falsification (SSDF) attacks by providing false spectrum reports. Existing solutions to detect such malicious behaviors cannot be utilized in scenarios where the transmission range of primary users is limited within a small sub-region of the CRN. In this paper, we present a framework for trustworthy collaboration in spectrum sensing for ad hoc CRNs. This framework incorporates a semi-supervised spatio-spectral anomaly/outlier detection system and a reputation system, both designed to detect byzantine attacks in the form of SSDF from malicious nodes within the CRN. The framework guarantees protection of incumbent primary users’ communication rights while at the same time making optimal use of the spectrum when it is not used by primary users. Simulation carried out under typical network conditions and attack scenarios shows that our proposed framework can achieve spectrum decision accuracy up to 99.3 % and detect malicious nodes up to 98 % of the time.

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Notes

  1. 1.

    We use the terms outlier detection and anomaly detection interchangeably.

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Correspondence to Muhammad Faisal Amjad.

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Amjad, M.F., Aslam, B., Attiah, A. et al. Towards trustworthy collaboration in spectrum sensing for ad hoc cognitive radio networks. Wireless Netw 22, 781–797 (2016). https://doi.org/10.1007/s11276-015-1004-2

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Keywords

  • Cognitive radio networks
  • Spectrum sensing
  • Reputation system
  • Outlier detection
  • Byzantine attack