Privacy, trust, and secure rewarding in mobile crowd-sensing based spectrum monitoring

Abstract

Mobile crowd-sensing (MCS) is a solution to provide spectrum availability information for dynamic spectrum access in cognitive radio systems. In MCS-based spectrum monitoring, participants should report the location and time of spectrum sensing in addition to the status of the spectrum bands, which raises the need for privacy-preserving. On the other hand, it is required to mitigate the possibility of fake reports sent from malicious participants that is almost handled using trust mechanisms. The trust mechanisms should be resistant to possible wrong reports which are due to channel fading and/or noise too. Moreover, some incentive mechanisms are required to encourage mobile users to participate in the crowd-sensing process. However, preserving-privacy, managing trust, and providing proper incentive mechanisms altogether is a challenge in MCS-based spectrum monitoring systems that has not been appropriately considered yet in previous work. In this paper, we propose a method that includes a privacy-preserving protocol with secure rewarding capability as well as a trust mechanism against malicious participants for MCS-based spectrum monitoring. We exploit Dempster–Shafer theory besides the reputation of participants in an anonymous manner to decide about spectrum availability. Also, we take advantage of the Gompertz function when updating the reputation of participants to better handle the spectrum sensing errors. To evaluate the proposed method, we conduct simulations to analyze and compare the proposed trust and spectrum decision mechanisms. The results show that in the proposed method, although 40% of participants were malicious, in more than 95% of cases, we were able to make the right decision about the participant's behavior compared to the majority method where only in about 85% of cases, the decision was correct. Also, we use ProVerif automatic protocol verifier to formally evaluate some security features of the proposed anonymity protocol. Moreover, we conduct some experimental analysis to validate the proposed protocol. The evaluation results demonstrate the superiority of the proposed method regarding both performance criteria and security features compared to the baseline methods.

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Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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Correspondence to Behrouz Shahgholi Ghahfarokhi.

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Hajian, G., Shahgholi Ghahfarokhi, B., Asadi Vasfi, M. et al. Privacy, trust, and secure rewarding in mobile crowd-sensing based spectrum monitoring. J Ambient Intell Human Comput (2021). https://doi.org/10.1007/s12652-021-03318-2

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Keywords

  • Crowd sensing
  • Reputation
  • Privacy
  • Spectrum monitoring
  • Secure rewarding