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Open AccessProceedings ArticleDOI

The new Casper: query processing for location services without compromising privacy

TLDR
Zhang et al. as mentioned in this paper presented Casper1, a new framework in which mobile and stationary users can entertain location-based services without revealing their location information, which consists of two main components, the location anonymizer and the privacy-aware query processor.
Abstract
This paper tackles a major privacy concern in current location-based services where users have to continuously report their locations to the database server in order to obtain the service. For example, a user asking about the nearest gas station has to report her exact location. With untrusted servers, reporting the location information may lead to several privacy threats. In this paper, we present Casper1; a new framework in which mobile and stationary users can entertain location-based services without revealing their location information. Casper consists of two main components, the location anonymizer and the privacy-aware query processor. The location anonymizer blurs the users' exact location information into cloaked spatial regions based on user-specified privacy requirements. The privacy-aware query processor is embedded inside the location-based database server in order to deal with the cloaked spatial areas rather than the exact location information. Experimental results show that Casper achieves high quality location-based services while providing anonymity for both data and queries.

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Citations
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Proceedings ArticleDOI

A grid-based location privacy-preserving method for LBS users

TL;DR: A grid-based location cloaking method based on k-anonymity model is proposed, which is expected to produce better quality of service by reducing the cloaking time and cloaked spatial region.
Book ChapterDOI

Privacy Issues in Edge Computing

TL;DR: By offloading some of the computational power and storage to the edge of the network, edge computing is capable to deliver new services and applications to billions of IoT devices, such as augmented reality, video analytics, smart home, smart hospital, Internet of vehicles, etc.
Book ChapterDOI

Context quality and privacy - friends or rivals?

TL;DR: It is argued that quality aspects in context model based systems should include and embed privacy protection and control mechanism as an integral part on all levels therefore increasing the usability of such systems from a user's point of view.

Revision en privacidad en servicios basados en localizacion

TL;DR: This dissertation aims to provide a history of computer science in Colombia from 1989 to 2002, a period chosen in order to explore its roots as well as specific cases up to and including the year of Colombia's independence from the United States.
References
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Journal ArticleDOI

k -anonymity: a model for protecting privacy

TL;DR: The solution provided in this paper includes a formal protection model named k-anonymity and a set of accompanying policies for deployment and examines re-identification attacks that can be realized on releases that adhere to k- anonymity unless accompanying policies are respected.
Proceedings ArticleDOI

Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking

TL;DR: A middleware architecture and algorithms that can be used by a centralized location broker service that adjusts the resolution of location information along spatial or temporal dimensions to meet specified anonymity constraints based on the entities who may be using location services within a given area.
Journal ArticleDOI

Protecting respondents identities in microdata release

TL;DR: This paper addresses the problem of releasing microdata while safeguarding the anonymity of respondents to which the data refer and introduces the concept of minimal generalization that captures the property of the release process not distorting the data more than needed to achieve k-anonymity.
Journal ArticleDOI

Achieving k -anonymity privacy protection using generalization and suppression

TL;DR: This paper provides a formal presentation of combining generalization and suppression to achieve k-anonymity and shows that Datafly can over distort data and µ-Argus can additionally fail to provide adequate protection.
Journal ArticleDOI

Location privacy in pervasive computing

TL;DR: The mix zone is introduced-a new construction inspired by anonymous communication techniques-together with metrics for assessing user anonymity, based on frequently changing pseudonyms.
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