{"title":"地理位置推理攻击:从建模到隐私风险评估(短文)","authors":"Miguel Núñez del Prado Cortez, Jesus Frignal","doi":"10.1109/EDCC.2014.32","DOIUrl":null,"url":null,"abstract":"Despite the commercial success of Location-Based Services (LBS), the sensitivity of the data they manage, specially those concerning the user's location, makes them a suitable target for geo-location inference attacks. These attacks are a new variant of traditional inference attacks aiming at disclosing personal aspects of users' life from their geo-location datasets. Since this threat might dramatically compromise the privacy of users, and so the confidence of LBS, a deeper knowledge of geo-location inference attacks becomes essential to protect LBS. To contribute to this goal, this short paper makes a step forward to model well-known types of geo-location inference attacks as a previous step to quantitatively assess the privacy risk they pose.","PeriodicalId":364377,"journal":{"name":"2014 Tenth European Dependable Computing Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Geo-Location Inference Attacks: From Modelling to Privacy Risk Assessment (Short Paper)\",\"authors\":\"Miguel Núñez del Prado Cortez, Jesus Frignal\",\"doi\":\"10.1109/EDCC.2014.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite the commercial success of Location-Based Services (LBS), the sensitivity of the data they manage, specially those concerning the user's location, makes them a suitable target for geo-location inference attacks. These attacks are a new variant of traditional inference attacks aiming at disclosing personal aspects of users' life from their geo-location datasets. Since this threat might dramatically compromise the privacy of users, and so the confidence of LBS, a deeper knowledge of geo-location inference attacks becomes essential to protect LBS. To contribute to this goal, this short paper makes a step forward to model well-known types of geo-location inference attacks as a previous step to quantitatively assess the privacy risk they pose.\",\"PeriodicalId\":364377,\"journal\":{\"name\":\"2014 Tenth European Dependable Computing Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-05-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Tenth European Dependable Computing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDCC.2014.32\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Tenth European Dependable Computing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDCC.2014.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Geo-Location Inference Attacks: From Modelling to Privacy Risk Assessment (Short Paper)
Despite the commercial success of Location-Based Services (LBS), the sensitivity of the data they manage, specially those concerning the user's location, makes them a suitable target for geo-location inference attacks. These attacks are a new variant of traditional inference attacks aiming at disclosing personal aspects of users' life from their geo-location datasets. Since this threat might dramatically compromise the privacy of users, and so the confidence of LBS, a deeper knowledge of geo-location inference attacks becomes essential to protect LBS. To contribute to this goal, this short paper makes a step forward to model well-known types of geo-location inference attacks as a previous step to quantitatively assess the privacy risk they pose.