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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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Journal ArticleDOI

Efficient Location Privacy-Preserving k-Anonymity Method Based on the Credible Chain

TL;DR: A new location privacy-preserving k-anonymity method based on the credible chain with two major features: the optimal k value for the current user is determined according to the user’s environment and social attributes and the method guarantees 100% QoS.
Book ChapterDOI

Location Privacy via Geo-Indistinguishability

TL;DR: The starting point of the approach is the principle of geo-indistinguishability, a formal notion of privacy that protects the user's exact location, while allowing approximate information --- typically needed to obtain a certain desired service --- to be released.
Proceedings Article

LinkDroid: reducing unregulated aggregation of app usage behaviors

TL;DR: A linkability-aware extension to current-mobile operating systems, called LinkDroid, which provides runtime monitoring and mediation of linkability across different apps, and proposes a client-side solution and compatible with the existing smartphone ecosystem.
Journal ArticleDOI

A Survey on Privacy in Location-Based Services

TL;DR: A compendium of techniques to protect the location privacy of the users, and an approach to compare and evaluate the presented mechanisms and their viability to be used in different kinds of location-based services is presented in this paper.
Dissertation

Enhancing communication privacy using trustworthy remote entities

Andrew Paverd
TL;DR: This thesis introduces the concept of the Trustworthy Remote Entity (TRE), an intermediary between distrusting participants that performs privacy-enhancing computations on the exchanged information that can be used to enhance communication privacy in location-based services and wireless network roaming.
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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