Research on Path Privacy Protection of Mobile Crowdsourcing System in Swarm Intelligence Aware Networks
Crowdsourcing has attracted attention from all sectors of society since it was proposed.The rapid development of intelligent control in the era of big data also provides favorable conditions for the execution of crowdsourcing tasks.Crowdsourcing tasks can be completed more quickly and effec-tively.These advantages also determine that crowdsourcing will become the research focus of many scholars inevitably.However,in order to avoid some security risks,participants expect to provide as lit-tle personal information as possible during the whole execution process of the crowdsourcing task.There-fore,ensuring the security of private data while performing crowdsourcing tasks smoothly is the primary consideration in the design of crowdsourcing mechanism.Therefore,this paper firstly describes crowd-sourcing and its workflow,mathematical definition and implementation mechanism of differential privacy.Secondly,it analyzes the application of differential privacy in different crowdsourcing scenarios.Finally,the differential privacy histogram construction algorithm based on order preserving regression is applied to real data sets.Through comparative analysis,the final experimental results show that the histogram data constructed by this algorithm has higher accuracy.
NETL
NSTL
万方数据
