{"title":"对IMU步态数据的隐私侵犯","authors":"Sanka Rasnayaka, T. Sim","doi":"10.1109/IJCB48548.2020.9304922","DOIUrl":null,"url":null,"abstract":"Modern personal devices measure and store vast amounts of sensory data such as Inertial Measurement Unit (IMU) data. These on-body sensor data can be used as a biometric by observing human movement (gait). People are less cautious about privacy vulnerabilities of such sensory data. We highlight which personal characteristics can be derived from on-body sensor data and the effect of sensor location towards these privacy invasions. By analyzing sensor locations with respect to privacy and utility we discover sensor locations which preserve utility such as biometric authentication while reducing privacy vulnerability. We have collected (1) a multi-stream on-body IMU dataset using 3 IMU sensors, consisting of 6 sensor locations, 6 actions along with various physical, personality and socio-economic characteristics from 53 participants. (2) an opinion survey of the relative importance of each attribute from 566 participants. Using these datasets we show that gait data reveals a lot of personal information, which maybe a privacy concern. The opinion survey reveals a ranking of the physical characteristics based on the perceived importance. Using a privacy vulnerability index we show that sensors located in the front pocket/wrist are more privacy invasive compared to back-pocket/bag which are less privacy invasive without a significant loss of utility as a biometric.","PeriodicalId":417270,"journal":{"name":"2020 IEEE International Joint Conference on Biometrics (IJCB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Your Tattletale Gait Privacy Invasiveness of IMU Gait Data\",\"authors\":\"Sanka Rasnayaka, T. Sim\",\"doi\":\"10.1109/IJCB48548.2020.9304922\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modern personal devices measure and store vast amounts of sensory data such as Inertial Measurement Unit (IMU) data. These on-body sensor data can be used as a biometric by observing human movement (gait). People are less cautious about privacy vulnerabilities of such sensory data. We highlight which personal characteristics can be derived from on-body sensor data and the effect of sensor location towards these privacy invasions. By analyzing sensor locations with respect to privacy and utility we discover sensor locations which preserve utility such as biometric authentication while reducing privacy vulnerability. We have collected (1) a multi-stream on-body IMU dataset using 3 IMU sensors, consisting of 6 sensor locations, 6 actions along with various physical, personality and socio-economic characteristics from 53 participants. (2) an opinion survey of the relative importance of each attribute from 566 participants. Using these datasets we show that gait data reveals a lot of personal information, which maybe a privacy concern. The opinion survey reveals a ranking of the physical characteristics based on the perceived importance. Using a privacy vulnerability index we show that sensors located in the front pocket/wrist are more privacy invasive compared to back-pocket/bag which are less privacy invasive without a significant loss of utility as a biometric.\",\"PeriodicalId\":417270,\"journal\":{\"name\":\"2020 IEEE International Joint Conference on Biometrics (IJCB)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Joint Conference on Biometrics (IJCB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCB48548.2020.9304922\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Joint Conference on Biometrics (IJCB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCB48548.2020.9304922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Your Tattletale Gait Privacy Invasiveness of IMU Gait Data
Modern personal devices measure and store vast amounts of sensory data such as Inertial Measurement Unit (IMU) data. These on-body sensor data can be used as a biometric by observing human movement (gait). People are less cautious about privacy vulnerabilities of such sensory data. We highlight which personal characteristics can be derived from on-body sensor data and the effect of sensor location towards these privacy invasions. By analyzing sensor locations with respect to privacy and utility we discover sensor locations which preserve utility such as biometric authentication while reducing privacy vulnerability. We have collected (1) a multi-stream on-body IMU dataset using 3 IMU sensors, consisting of 6 sensor locations, 6 actions along with various physical, personality and socio-economic characteristics from 53 participants. (2) an opinion survey of the relative importance of each attribute from 566 participants. Using these datasets we show that gait data reveals a lot of personal information, which maybe a privacy concern. The opinion survey reveals a ranking of the physical characteristics based on the perceived importance. Using a privacy vulnerability index we show that sensors located in the front pocket/wrist are more privacy invasive compared to back-pocket/bag which are less privacy invasive without a significant loss of utility as a biometric.