Location Privacy Preserving Task Assignment In Spatial Crowdsourcing

In recent years,with the rapid development of computer and communication technology,different spatial crowdsourcing platforms have emerged in real life scenes,such as Didi,Meituan takeout,etc.Different from the traditional crowdsourcing platform,spatial crowdsourcing platform needs to obtain the real location of crowdsourcing workers in the task assignment stage to achieve effective spatial crowdsourcing task assignment.Most of the spatial crowdsourcing platforms are untrustworthy such as leaking the location information of crowdsourcing workers for some reasons,which makes workers unwilling to participate in the task assignment on crowdsourcing platform.Therefore,it is particularly important to preserve workers' location privacy in spatial crowdsourcing.In addition to workers' location,the task location should also be preserved in the assignment stage,because the crowdsourcing platform may infer the worker's location information from the task assignment results and task information.In addition,how to ensure the quality of task assignment while preserving location privacy is also a key problem in spatial crowdsourcing.This paper studies how to ensure the quality of task assignment on the premise of preserving the location privacy of spatial tasks and crowdsourcing workers,and proposes a spatial crowdsourcing task assignment method based on location privacy protection.The main research work is as follows:(1)A location privacy preserving algorithm based on location transformation and spatial anonymity is proposed.Firstly,the location information of spatial tasks and crowdsourcing workers is transformed based on the location transformation method to preserve the location privacy of spatial tasks and crowdsourcing workers at the same time.Based on the distribution of crowdsourcing workers,the spatial anonymity technology is implemented based on clustering and adding noise data to further preserve the location privacy of crowdsourcing workers.(2)A two-stage task assignment method based on location privacy preserving and crowdsourcing worker type is proposed.Firstly,the comprehensive benefits of crowdsourcing workers are defined based on the travelling distance of crowdsourcing workers and the type of crowdsourcing workers.Secondly,a two-stage task assignment method is proposed to maximize the comprehensive benefits of crowdsourcing workers under the condition of location privacy preserving.Firstly,the initial crowdsourcing worker set matching the task is obtained based on location privacy preserving;Then,by analyzing the historical task data of crowdsourcing workers,the type of crowdsourcing workers is divided,and based on the type of crowdsourcing workers and historical task data,the probability of crowdsourcing workers accepting the task or the expected reward value is predicted to obtain the comprehensive benefits of crowdsourcing workers;Finally,the task is assigned to maximize the comprehensive benefits of crowdsourcing workers.(3)In this paper,the real data set is selected as the experimental data set,and the proposed location privacy preserving algorithm and task assignment algorithm are tested and verified respectively.The experimental results show the effectiveness of the proposed method.