{"title":"Anonymity-Preserving Location Data Publishing","authors":"Girish Lingappa, Ying Cai","doi":"10.1109/ICCCN.2008.ECP.111","DOIUrl":null,"url":null,"abstract":"The advances in wireless communication and positioning technology have made it possible to collect large volumes of personal location data. While such data are useful to many organizations, making them public accessible is generally prohibited, because location data may imply sensitive private information. This paper investigates the challenges of publishing location data while preserving the location privacy of data subjects. Since location data itself may lead to subject reidentification, simply removing user identity of location data is not sufficient for anonymity preservation. To address this problem, this paper presents a novel technique that reduces location resolution to achieve a desired level of anonymity protection. The new scheme ensures K-anonymity protection and allows location data to be published as accurate as possible. More importantly, it is designed to support efficient publishing of large volumes of location data.","PeriodicalId":314071,"journal":{"name":"2008 Proceedings of 17th International Conference on Computer Communications and Networks","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Proceedings of 17th International Conference on Computer Communications and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCN.2008.ECP.111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The advances in wireless communication and positioning technology have made it possible to collect large volumes of personal location data. While such data are useful to many organizations, making them public accessible is generally prohibited, because location data may imply sensitive private information. This paper investigates the challenges of publishing location data while preserving the location privacy of data subjects. Since location data itself may lead to subject reidentification, simply removing user identity of location data is not sufficient for anonymity preservation. To address this problem, this paper presents a novel technique that reduces location resolution to achieve a desired level of anonymity protection. The new scheme ensures K-anonymity protection and allows location data to be published as accurate as possible. More importantly, it is designed to support efficient publishing of large volumes of location data.