Privacy-Preserving Collaborative Spectrum Sensing With Multiple Service Providers


In cognitive radio networks (CRNs), collaborative sensing has been considered an engaging suggests that to improving spectrum sensing performance. But, privacy issues arise when multiple service providers (SPs) collaborate on learning the spectrum availabilities. Specifically, sharing sensing knowledge might enable malicious SPs or secondary users (SUs) to geolocate an SU using existing localization techniques. These malicious entities may be untrusted SPs/SUs or external attackers that compromise SPs/SUs. To incentivize SUs to contribute their sensing knowledge, the privacy of every SU should be guaranteed. In this paper, we have a tendency to propose a privacy preservation framework called PrimCos for multi-SP collaborative sensing, which addresses many competing challenges not however thought of within the literature, that is, being compatible with general collaborative sensing schemes, providing privacy guarantee for each SU and making certain worst case privacy protection beneath collusion. Each analytical and numerical results show that the proposed framework provides privacy protection for every SU with controllable impact on the sensing performance under completely different varieties of attacks.

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