Affirmed Crowd Sensor Selection based Cooperative Spectrum Sensing

The Cooperative Spectrum sensing model is gaining importance among the cognitive radio network sharing groups. While the crowd-sensing model (technically the cooperative spectrum sensing) model has positive developments, one of the critical challenges plaguing the model is the false or manipulated crowd sensor data, which results in implications for the secondary user’s network. Considering the efficacy of the spectrum sensing by crowd-sensing model, it is vital to address the issues of falsifications and manipulations, by focusing on the conditions of more accurate determination models. Concerning this, a method of avoiding falsified crowd sensors from the process of crowd sensors centric cooperative spectrum sensing has portrayed in this article. The proposal is a protocol that selects affirmed crowd sensor under diversified factors of the decision credibility about spectrum availability. An experimental study is a simulation approach that evincing the competency of the proposal compared to the other contemporary models available in recent literature

Secure crowdsourcing-based cooperative pectrum sensing

Cooperative (spectrum) sensing is a key function for dynamic spectrum access and is essential for avoiding interference with licensed primary users and identifying spectrum holes. A promising approach for effective cooperative sensing over a large geographic region is to rely on special spectrum-sensing providers (SSPs), which outsource spectrum-sensing tasks to distributed mobile users. Its feasibility is deeply rooted in the ubiquitous penetration of mobile devices into everyday life. Crowdsourcing-based cooperative spectrum sensing is, however, vulnerable to malicious sensing data injection attack, in which a malicious CR users submit false sensing reports containing power measurements much larger (or smaller) than the true value to inflate (or deflate) the final average, in which case the SSP may falsely determine that the channel is busy (or vacant). In this paper, we propose a novel scheme to enable secure crowdsourcing-based cooperative spectrum sensing by jointly considering the instantaneous trustworthiness of mobile detectors in combination with their reputation scores during data fusion. Our scheme can enable robust cooperative sensing even if the malicious CR users are the majority. The efficacy and efficiency of our scheme have been confirmed by extensive simulation studies. © 2013 IEEE

HSCI2013: proceedings of the 10th International Conference on Hands-on Science

The core topic of the 10th Hands-on Science Conference is "Educating for Science and through Science"Livro de trabalhos extensos aceites para publicação no livro de proceedings da 10ª conferencia HSC