Mobile　crowdsensing　is　a　typical　application　of　the　Industrial　Internet　of　hings　and　brings　a　promising　opportunity　to　construct　powerful　industrial　systems　and　services.　The　existing　privacy　protection　schemes　usually　adopt　a　unified　privacy　protection　policy　for　all　sensing　data　due　to　lack　of　effective　privacy　metrics,　thereby　resulting　in　excessive　or　insufficient　protection　of　privacy　information　and　low　accuracy　of　sensing　data.　To　tackle　these　issues,　in　this　paper,　we　propose　a　personalized　privacy　protection　data　uploading　(PPDU)　scheme　based　on　game　theory　and　sensing　user＇s　historical　spatio-temporal　data.　In　PPDU,　a　personalized　privacy　measurement　algorithm　is　designed　to　obtain　the　personalized　privacy　degree　of　user　sensing　data.　Based　on　the　privacy　degree,　a　user　uploading　behavior　game　is　designed　by　employing　an　incomplete　information　game,　and　a　game-based　spatio-temporal　sensing　data　uploading　method　is　proposed　for　user　privacy　protection.　Simulation　experiments　with　real　trajectory　data　show　that　the　PPDU　scheme　makes　a　reasonable　balance　between　retaining　high　quality　of　crowdsensing　service　and　protecting　user＇s　privacy.　©　2019　IEEE.