{"title":"Geopriv4j","authors":"Liyue Fan, S. Gunja","doi":"10.1145/3403896.3403968","DOIUrl":null,"url":null,"abstract":"The breach of users' location privacy can be catastrophic. To prevent privacy breaches, numerous location privacy methods have been developed in the last two decades. However, they have not been widely adopted in location-based applications. As a result, users' true location data is directly shared with untrusted service providers or researchers, raising concerns about location privacy. In this paper, we describe our effort to develop an open source repository, named Geopriv4j, in order to facilitate the adoption of location privacy methods in location-based services and research studies. Geopriv4j emphasizes on the practicality of location privacy, by identifying local, on-the-fly privacy methods under multiple categories. To facilitate adoption, Geopriv4j unifies the implementation of location privacy in Java, and provides usage examples as well as a sample Android app. To validate our implementation, we evaluate the location privacy methods in Geopriv4j with CPU, memory, and run time measures, using synthetically generated location traces.","PeriodicalId":433637,"journal":{"name":"Proceedings of the Sixth International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixth International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3403896.3403968","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The breach of users' location privacy can be catastrophic. To prevent privacy breaches, numerous location privacy methods have been developed in the last two decades. However, they have not been widely adopted in location-based applications. As a result, users' true location data is directly shared with untrusted service providers or researchers, raising concerns about location privacy. In this paper, we describe our effort to develop an open source repository, named Geopriv4j, in order to facilitate the adoption of location privacy methods in location-based services and research studies. Geopriv4j emphasizes on the practicality of location privacy, by identifying local, on-the-fly privacy methods under multiple categories. To facilitate adoption, Geopriv4j unifies the implementation of location privacy in Java, and provides usage examples as well as a sample Android app. To validate our implementation, we evaluate the location privacy methods in Geopriv4j with CPU, memory, and run time measures, using synthetically generated location traces.