The new Casper: query processing for location services without compromising privacy
Mohamed F. Mokbel,Chi-Yin Chow,Walid G. Aref +2 more
- pp 763-774
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
Citations
More filters
Book ChapterDOI
Air Traffic Analysis.
Journal ArticleDOI
Range-Based Nearest Neighbor Queries with Complex-Shaped Obstacles
TL;DR: An efficient algorithm is proposed, which exploits the OB-tree and a binary traversal order of data objects to accelerate query processing of RONN, and the experimental result shows that the RRONN-OBA algorithm outperforms the two R-tree based algorithms and RONn-OA significantly.
Proceedings ArticleDOI
Disclosure-Free GPS Trace Search in Smartphone Networks
TL;DR: This paper presents a powerful distributed framework for finding similar trajectories in a smart phone network, without disclosing the traces of participating users, and reveals that Smart Trace computes the desired results with 74% less energy consumption and 13% faster than its centralized and decentralized counterparts.
Journal ArticleDOI
Privacy Challenges With Protecting Live Vehicular Location Context
TL;DR: This work investigates the privacy surface of a vehicle by considering the many different ways in which location privacy can be leaked and identifies techniques to protect privacy and concludes that location privacy is insufficient to provide location privacy against a single threat vector.
Journal ArticleDOI
Achieving User-Defined Location Privacy Preservation Using a P2P System
TL;DR: An encoding scheme of users’ identifiers and a fully distributed architecture are designed and a privacy preservation scheme based on them are proposed that can satisfy different strengths of privacy preservation required by each user even under the most severe scenarios.
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
Marco Gruteser,Dirk Grunwald +1 more
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.