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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

Pystin: Enabling Secure LBS in Smart Cities With Privacy-Preserving Top- $k$ Spatial–Textual Query

TL;DR: Detailed security analyzes show that the proposed Pystin scheme is indeed a privacy-preserving $\text{T}{k}$ SK query scheme, and results confirm the scalability, efficiency properties of this proposed PyStin scheme.
Journal ArticleDOI

The Digital Marauder's Map: A WiFi Forensic Positioning Tool

TL;DR: The digital Marauder's map, a forensic surveillance tool for wireless networks, can reveal the locations of WiFi-enabled mobile devices within the coverage area of a high-gain antenna.
Proceedings ArticleDOI

ReverseCloak: Protecting Multi-level Location Privacy over Road Networks

TL;DR: ReverseCloak is presented, a new class of reversible location cloaking mechanisms that effectively support multi-level location privacy, allowing selective de-anonymization of the cloaking region to reduce the granularity of the perturbed location when suitable access credentials are provided.
Journal ArticleDOI

Crowdsensing Multimedia Data: Security and Privacy Issues

TL;DR: Security and privacy issues in multimedia crowdsensing are identified and existing solutions that are designed to protect both data producers and consumers in multimedia communities are described.
Journal ArticleDOI

Towards practical private processing of database queries over public data

TL;DR: This work enables private querying on public data services so that the contents of user queries and any user data are hidden and therefore not revealed to the online service providers, and proposes two protocols for private processing of database queries, namely BHE and HHE.
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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