PROJECT TITLE :

Privacy-Preserving Crowdsourced Spectrum Sensing - 2018

ABSTRACT:

Dynamic spectrum access is promising for mitigating worldwide wireless spectrum shortage. Crowdsourced spectrum sensing (CSS) refers to recruiting ubiquitous mobile users to perform real-time spectrum sensing at specified locations and has nice potential in mitigating the drawbacks of current spectrum database operations. While not sturdy incentives and site privacy protection in place, however, mobile users can be reluctant to act as mobile crowdsourcing workers for spectrum-sensing tasks. In this Project, we tend to 1st formulate participant selection in CSS systems as a reverse auction problem, in which every participant's true cost for spectrum sensing is closely tied to his current location. Then, we tend to demonstrate how the situation privacy of CSS participants will be easily breached beneath the framework. Finally, we tend to gift PriCSS, a completely unique framework for a CSS service supplier to pick out CSS participants in an exceedingly differentially privacy-preserving manner. During this framework, we have a tendency to propose PriCSS-and PriCSS+, two totally different schemes under distinct style objectives and assumptions. PriCSS-is an approximately truthful theme that achieves differential location privacy and an approximate minimum payment, whereas PriCSS+may be a truthful theme that achieves differential location privacy and an approximate minimum social price. The detailed theoretical analysis and simulation studies are performed to demonstrate the efficacy of both schemes.