{"title":"Pseudonym exchange for privacy-preserving publishing of trajectory data set","authors":"K. Mano, Kazuhiro Minami, H. Maruyama","doi":"10.1109/GCCE.2014.7031175","DOIUrl":null,"url":null,"abstract":"Anonymization is a common technique for publishing a location data set in a privacy-preserving way. However, such an anonymized data set lacks trajectory information of users, which could be beneficial to many location-based analytic services. In this paper, we present a dynamic pseudonym scheme for constructing alternate possible paths of mobile users to protect their location privacy. We introduce a formal definition of location privacy for pseudonym-based location data sets and develop a polynomial-time verification algorithm for determining whether each user in a given location data set has sufficient number of possible paths to disguise the user's true movements. We also provide the correctness proof of the algorithm.","PeriodicalId":145771,"journal":{"name":"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCCE.2014.7031175","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Anonymization is a common technique for publishing a location data set in a privacy-preserving way. However, such an anonymized data set lacks trajectory information of users, which could be beneficial to many location-based analytic services. In this paper, we present a dynamic pseudonym scheme for constructing alternate possible paths of mobile users to protect their location privacy. We introduce a formal definition of location privacy for pseudonym-based location data sets and develop a polynomial-time verification algorithm for determining whether each user in a given location data set has sufficient number of possible paths to disguise the user's true movements. We also provide the correctness proof of the algorithm.