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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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Quantifying and mitigating privacy threats in wireless protocols and services

TL;DR: The design and evaluation of an 802.11-like wireless link layer protocol that obfuscates all transmitted bits, rather than select fields, to increase privacy is presented, which is nearly as efficient as existing schemes for discovery, link setup, and data delivery because transmission requires only symmetric key encryption and reception requires a table lookup followed by asymmetric key decryption.
Journal ArticleDOI

An efficient method for privacy preserving location queries

TL;DR: The privacy persevering location query (PLQ), an efficient privacy preserving location query processing framework, is proposed, which can enable the location-based query without revealing user location information.
Journal ArticleDOI

Protecting User Privacy Better with Query l-Diversity

TL;DR: The authors propose two techniques: Expand Cloak and Hilbert Cloak to achieve query l-diversity, which better protect user privacy and compare the improved Interval Cloak technique through extensive simulation studies.
Journal ArticleDOI

A Novel Personalized TTP-free Location Privacy Preserving Method

TL;DR: A novel TTP(Trusted Third Party)-free location privacy preserving method that can satisfy k-anonymity, ldiversity and cloaking granularity simultaneously for privacy preserving is proposed.
Journal ArticleDOI

A Privacy Preserving Framework for Worker’s Location in Spatial Crowdsourcing Based on Local Differential Privacy

Jiazhu Dai, +1 more
- 14 Jun 2018 - 
TL;DR: A new location privacy protection framework based on local difference privacy for spatial crowdsourcing is proposed, which does not require the participation of trusted third parties by adding noises locally to workers’ locations.
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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