Privacy-Preserving Task Allocation Based on QoS in Crowd Sensing

Abstract

Crowd sensing, an important research direction in wireless communication, realizes the allocation and collection of tasks through the smart devices carried by users. However, in the task allocation process, how to protect user privacy from being leaked and select high-quality users to guarantee the quality of task completion are two major challenges. Particularly, individual quality of service (QoS) affects the quality of the task completion. In this paper, we propose a differentially private task allocation scheme. During the process of task allocation, differential privacy is utilized for the location privacy protection. In addition, in order to reduce unnecessary privacy leakage, we simplify the task allocation process and select users with higher QoS to guarantee the QoS of task. Security analysis and experimental results state that our scheme provides differential privacy protection while ensuring QoS of tasks.