scispace - formally typeset
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.

read more

Content maybe subject to copyright    Report

Citations
More filters
Posted Content

Security and Privacy in Vehicular Social Networks

TL;DR: It is shown existing solutions can in fact evolve and address the VSN-specific challenges, and improve or even accelerate the adoption of VSN applications.
Proceedings ArticleDOI

Secure KNN Queries over Encrypted Data: Dimensionality Is Not Always a Curse

TL;DR: It is shown that increasing the data dimensionality via LSH is indeed helpful to tackle 2DSkNN problem and 2D SkNN achieves adaptive indistinguishability under chosen-keyword attack (IND2-CKA) secure in the random oracle model.
Journal ArticleDOI

An Efficient and Privacy-Preserving Multiuser Cloud-Based LBS Query Scheme

TL;DR: This paper encrypts LBS data and LBS queries with a hybrid encryption mechanism, which can efficiently implement privacy-preserving search over encrypted LBSData and is very suitable for the multiuser setting with secure and effective user enrollment and user revocation.
Proceedings ArticleDOI

Adaptive Location Privacy with ALP

TL;DR: Adaptive Location Privacy (ALP) as mentioned in this paper is a new framework enabling the dynamic configuration of LPPMs, which can be used in two scenarios: (1) offline, where a system designer can choose and automatically tune the most appropriate LPPM for the protection of a given dataset, (2) online, where the user of a crowd sensing application can protect consecutive batches of her geolocated data by automatically tuning a given LPPM to fulfil a set of privacy and utility objectives.

Schutz der Privatsphäre in kontext- und ortsbezogenen Diensten

TL;DR: Ein Ontologie-basiertes Kontextmodell entwickelt, auf dessen Grundlage die Definition and konsistente Durchsetzung situationsabhangiger Freigaberegeln moglich ist, wird eine vollstandige Systemarchitektur zur Kontextverwaltung sowie deren Integration in ein mobiles Betriebssystem beschrieben.
References
More filters
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.
Related Papers (5)