A spatial crowdsourcing quality control model is based on location privacy protection and decessor detection
A privacy protection and control model technology, applied in the field of spatial crowdsourcing, can solve problems such as easy expansion of research conclusions, error rate, and lack of seriousness
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[0104] A spatial crowdsourcing quality control model based on location privacy protection and cheater detection of the present invention specifically includes the following steps:
[0105] S1. Privacy protection model based on spatial anonymity technology
[0106] S1.1 Spatial crowdsourcing position k anonymous
[0107] In spatial crowdsourcing, the location attributes of workers are used as quasi-identifiers. In spatially anonymous regions, the position of any worker in spatial crowdsourcing cannot be distinguished from the positions of at least k − 1 other workers. Among them, the quasi-identifier is the minimum attribute set that combines other external information to identify the target location with a high probability. like image 3 As shown, the real location of crowdsourcing workers in a certain space is L, and after using k anonymity, the location point L is expanded into a hidden area R to replace the exact location information of workers. In this spatial hidden a...
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