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
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Book ChapterDOI
A Predictive Differentially-Private Mechanism for Mobility Traces
TL;DR: The notion of geo-indistinguishability was recently introduced, adapting the well-known concept of Differential Privacy to the area of location-based systems, and a Laplace-based obfuscation mechanism satisfying this privacy notion works well.
Proceedings ArticleDOI
K-Anonymization as Spatial Indexing: Toward Scalable and Incremental Anonymization
TL;DR: A novel approach to k-Anonymization is introduced by making a new observation of a strikingly similar parallel between database indexing and k-anonymity, and suggesting multidimensional spatial indexing as the basis for anonymization.
Journal ArticleDOI
User-Defined Privacy Grid System for Continuous Location-Based Services
TL;DR: Experimental results show that the DGS is more efficient than the state-of-the-art privacy-preserving technique for continuous LBS, and can be easily extended to support other spatial queries without changing the algorithms run by the semi-trusted third party and the database server.
Journal ArticleDOI
The Long Road to Computational Location Privacy: A Survey
TL;DR: The protection mechanisms between online and offline use cases are divided into six categories depending on the nature of their algorithm, and the evaluation metrics used to assess protection mechanisms in terms of privacy, utility and performance are surveyed.
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Probabilistic Reverse Nearest Neighbor Queries on Uncertain Data
TL;DR: An efficient algorithm based on various novel pruning approaches that solves the probabilistic RNN queries on multidimensional uncertain data and is even more efficient than a sampling-based approximate algorithm for most of the cases and is highly scalable.
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