Research on Key Technologies of Collaborative Spectrum Sensing Based on Differential Privacy

Aiming at the incentive mechanism issues in collaborative spectrum sensing and access for privacy protection in Internet of Things (IoT) crowd sensing, a multi-task winner selection mechanism based on differential privacy is proposed to address the privacy leakage in Mobile Crowd Sensing (MCS). This mechanism utilizes the exponential mechanism of differential privacy to select winners, protecting the cost privacy information of Crowd Sense Users (CSUs). Furthermore, to incentivize CSUs, a two-layer Stackelberg game algorithm is proposed. This algorithm can coordinate the compensation paid by Secondary Users (SUs) for spectrum access and the data quality reported by CSUs, thereby effectively enhancing the enthusiasm of CSUs to participate in sensing and the performance of collaborative spectrum detection. Simulation results using MATLAB software show that compared to traditional methods, the proposed algorithm increases the average user reward by $19.5 \%$.