A Framework for Generating Network-Based Moving Objects
Geoinformatica
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Location Privacy in Pervasive Computing
IEEE Pervasive Computing
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Achieving k-anonymity privacy protection using generalization and suppression
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Data Privacy through Optimal k-Anonymization
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
Location Privacy in Mobile Systems: A Personalized Anonymization Model
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Mondrian Multidimensional K-Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
k-Anonymity in Databases with Timestamped Data
TIME '06 Proceedings of the Thirteenth International Symposium on Temporal Representation and Reasoning
Achieving anonymity via clustering
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
On the efficiency of checking perfect privacy
Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Personalized privacy preservation
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
(α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
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
PRIVE: anonymous location-based queries in distributed mobile systems
Proceedings of the 16th international conference on World Wide Web
M-invariance: towards privacy preserving re-publication of dynamic datasets
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Preventing Location-Based Identity Inference in Anonymous Spatial Queries
IEEE Transactions on Knowledge and Data Engineering
Anonymity in Location-Based Services: Towards a General Framework
MDM '07 Proceedings of the 2007 International Conference on Mobile Data Management
Enabling private continuous queries for revealed user locations
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Protecting privacy against location-based personal identification
SDM'05 Proceedings of the Second VDLB international conference on Secure Data Management
Secure anonymization for incremental datasets
SDM'06 Proceedings of the Third VLDB international conference on Secure Data Management
Longitude: Centralized Privacy-Preserving Computation of Users' Proximity
SDM '09 Proceedings of the 6th VLDB Workshop on Secure Data Management
Preserving location and absence privacy in geo-social networks
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
The VLDB Journal — The International Journal on Very Large Data Bases
Measuring query privacy in location-based services
Proceedings of the second ACM conference on Data and Application Security and Privacy
Transactions on Data Privacy
Exploring dependency for query privacy protection in location-based services
Proceedings of the third ACM conference on Data and application security and privacy
Protecting query privacy in location-based services
Geoinformatica
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Spatial generalisation has been recently proposed as a technique for the anonymisation of requests in location based services. This article provides a formal characterisation of a privacy attack that has been informally described in previous work, and presents a new generalisation algorithm that is proved to be a safe defense against that attack. The article also reports the results of an extensive experimental study, comparing the new algorithm with the ones that have been previously proposed in the literature.