{"title":"Maintaining anonymity using -privacy","authors":"D. Nussbaum, Masoud T. Omran, J. Sack","doi":"10.1080/17489725.2017.1363419","DOIUrl":null,"url":null,"abstract":"Abstract In this paper, we study potential inference attacks targeting location-based service (LBS) users. In particular, we introduce a new model for privacy protection, provides heuristic defence techniques to protect users’ privacy from such attacks, and present the results of experiments performed to evaluate the heuristics. Potential attackers who gain access to supplemental information may infer sensitive information such as location, identity or lifestyle about a user querying an LBS. Supplemental information used includes the times when queries are submitted, speed limits, and travel times for the underlying road network, or residential/commercial address directories. Our objective here is to prevent attackers from connecting external information to user queries. To address this objective, we introduce the notion of (i, j)-privacy. The novel (i, j)-privacy model generalises previous privacy models and allows users to customise their own privacy levels. To implement (i, j)-privacy, we have designed several heuristics. Although these are heuristic approaches, they do provide exact responses for user queries. We evaluate these heuristics experimentally on different road networks. We study the impact of a number of input parameters (mainly geometric) and present the results here. Our experiments demonstrate that, for realistic user settings, our algorithms provide results rapidly and of high quality.","PeriodicalId":44932,"journal":{"name":"Journal of Location Based Services","volume":"11 1","pages":"1 - 28"},"PeriodicalIF":1.2000,"publicationDate":"2017-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/17489725.2017.1363419","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Location Based Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17489725.2017.1363419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 3
Abstract
Abstract In this paper, we study potential inference attacks targeting location-based service (LBS) users. In particular, we introduce a new model for privacy protection, provides heuristic defence techniques to protect users’ privacy from such attacks, and present the results of experiments performed to evaluate the heuristics. Potential attackers who gain access to supplemental information may infer sensitive information such as location, identity or lifestyle about a user querying an LBS. Supplemental information used includes the times when queries are submitted, speed limits, and travel times for the underlying road network, or residential/commercial address directories. Our objective here is to prevent attackers from connecting external information to user queries. To address this objective, we introduce the notion of (i, j)-privacy. The novel (i, j)-privacy model generalises previous privacy models and allows users to customise their own privacy levels. To implement (i, j)-privacy, we have designed several heuristics. Although these are heuristic approaches, they do provide exact responses for user queries. We evaluate these heuristics experimentally on different road networks. We study the impact of a number of input parameters (mainly geometric) and present the results here. Our experiments demonstrate that, for realistic user settings, our algorithms provide results rapidly and of high quality.
期刊介绍:
The aim of this interdisciplinary and international journal is to provide a forum for the exchange of original ideas, techniques, designs and experiences in the rapidly growing field of location based services on networked mobile devices. It is intended to interest those who design, implement and deliver location based services in a wide range of contexts. Published research will span the field from location based computing and next-generation interfaces through telecom location architectures to business models and the social implications of this technology. The diversity of content echoes the extended nature of the chain of players required to make location based services a reality.