Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
Protecting privacy against location-based personal identification
SDM'05 Proceedings of the Second VDLB international conference on Secure Data Management
Providing K-Anonymity in location based services
ACM SIGKDD Explorations Newsletter
PCTA: privacy-constrained clustering-based transaction data anonymization
Proceedings of the 4th International Workshop on Privacy and Anonymity in the Information Society
Privacy preservation in the dissemination of location data
ACM SIGKDD Explorations Newsletter
Utility-guided Clustering-based Transaction Data Anonymization
Transactions on Data Privacy
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This paper introduces a privacy model for location based services that utilizes collected movement data to identify parts of the user trajectories, where user privacy is at an elevated risk. To protect the privacy of the user, the proposed methodology transforms the original requests into anonymous counterparts by offering trajectory K---anonymity. As a proof of concept, we build a working prototype that implements our solution approach and is used for experimentation and evaluation purposes. Our implementation relies on a spatial DBMS that carries out part of the necessary analysis. Through experiments we demonstrate the effectiveness of our approach to preserve the K---anonymity of the users for as long as the requested services are in progress.