Secure Task Assignment Based on Tentative Planned Path in Crowdsensing Systems

In recent years, with the development of mobile crowdsensing (MCS) technology, task assignment has been widely researches as one of the key steps. In existing scenarios, the path range of a task is often already determined. Workers who want to participate in a task need to submit their future planned paths. To address this situation, we propose a task assignment scheme based on the degree of matching of task paths as an evaluation metric. In order to protect the location information of task requesters and workers from being leaked during the task assignment process, we use CKKS encryption techniques that support multi-party homomorphism to protect their private information. Finally, we conducted security analysis and simulation experiments on the scheme, and the results show that our scheme is efficient in task assignment while the privacy information of workers and task requesters is protected.