k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
State-of-the-art in privacy preserving data mining
ACM SIGMOD Record
Location Privacy in Mobile Systems: A Personalized Anonymization Model
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Effective Density Queries on ContinuouslyMoving Objects
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
A peer-to-peer spatial cloaking algorithm for anonymous location-based service
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
Privacy-Preserving Data Mining on Moving Object Trajectories
MDM '07 Proceedings of the 2007 International Conference on Mobile Data Management
Protecting privacy against location-based personal identification
SDM'05 Proceedings of the Second VDLB international conference on Secure Data Management
You can walk alone: trajectory privacy-preserving through significant stays protection
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part I
Daisy: the center for data-intensive systems at Aalborg University
ACM SIGMOD Record
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In order to provide context--aware Location--Based Services, real location data of mobile users must be collected and analyzed by spatio--temporal data mining methods. However, the data mining methods need precise location data, while the mobile users want to protect their location privacy. To remedy this situation, this paper first formally defines novel location privacy requirements. Then, it briefly presents a system for privacy--preserving trajectory collection that meets these requirements. The system is composed of an untrusted server and clients communicating in a P2P network. Location data is anonymized in the system using data cloaking and data swapping techniques. Finally, the paper empirically demonstrates that the proposed system is effective and feasible.