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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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Trajectory Data Mining: An Overview

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Geo-indistinguishability: differential privacy for location-based systems

TL;DR: In this article, the authors introduce geoind, a formal notion of privacy for location-based systems that protects the user's exact location, while allowing approximate information -typically needed to obtain a certain desired service -to be released.
Proceedings ArticleDOI

Private queries in location based services: anonymizers are not necessary

TL;DR: This work proposes a novel framework to support private location-dependent queries, based on the theoretical work on Private Information Retrieval (PIR), which achieves stronger privacy for snapshots of user locations and is the first to provide provable privacy guarantees against correlation attacks.
Proceedings ArticleDOI

Secure kNN computation on encrypted databases

TL;DR: A new asymmetric scalar-product-preserving encryption (ASPE) that preserves a special type of scalar product and is shown to resist practical attacks of a different background knowledge level, at a different overhead cost.
References
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Proceedings ArticleDOI

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Blind evaluation of nearest neighbor queries using space transformation to preserve location privacy

TL;DR: The results show that the results very closely approximate the result set generated from performing KNN queries in the original space while enforcing the new location privacy metrics termed u-anonymity and a- anonymity, which are stronger and more generalized privacy measures than the commonly used K-anonymsity and cloaked region size measures.
Proceedings ArticleDOI

Location-based spatial queries

TL;DR: This paper proposes an approach that enables mobile clients to determine the validity of previous queries based on their current locations, and focuses on two of the most common spatial query types, namely nearest neighbor and window queries, define the validity region in each case and propose the corresponding query processing algorithms.
Journal ArticleDOI

Managing uncertainty in moving objects databases

TL;DR: This article proposes to model an uncertain trajectory as a three-dimensional (3D) cylindrical body and introduces a set of novel but natural spatio-temporal operators which capture the uncertainty and are used to express spatio/temporal range queries.
Proceedings ArticleDOI

A generic framework for monitoring continuous spatial queries over moving objects

TL;DR: This framework is the first to address the location update issue and to provide a common interface for monitoring mixed types of queries and significantly reduces the wireless communication and query reevaluation costs required to maintain the up-to-date query results.
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