Security-control methods for statistical databases: a comparative study
ACM Computing Surveys (CSUR)
A Framework for Generating Network-Based Moving Objects
Geoinformatica
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Novel Approaches in Query Processing for Moving Object Trajectories
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
On map-matching vehicle tracking data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Protecting Location Privacy Through Path Confusion
SECURECOMM '05 Proceedings of the First International Conference on Security and Privacy for Emerging Areas in Communications Networks
Mondrian Multidimensional K-Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Trajectory clustering: a partition-and-group framework
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Preserving privacy in gps traces via uncertainty-aware path cloaking
Proceedings of the 14th ACM conference on Computer and communications security
HERMES: aggregative LBS via a trajectory DB engine
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Privacy Preservation in the Publication of Trajectories
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
A privacy-aware trajectory tracking query engine
ACM SIGKDD Explorations Newsletter
Towards trajectory anonymization: a generalization-based approach
SPRINGL '08 Proceedings of the SIGSPATIAL ACM GIS 2008 International Workshop on Security and Privacy in GIS and LBS
Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Clustering uncertain trajectories
Knowledge and Information Systems
Proceedings of the 15th International Conference on Extending Database Technology
Semantic trajectories modeling and analysis
ACM Computing Surveys (CSUR)
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Existing approaches for privacy-aware mobility data sharing aim at publishing an anonymized version of the mobility dataset, operating under the assumption that most of the information in the original dataset can be disclosed without causing any privacy violations. In this paper, we assume that the majority of the information that exists in the mobility dataset must remain private and the data has to stay in-house to the hosting organization. To facilitate privacy-aware sharing of the mobility data we develop a trajectory query engine that allows subscribed users to gain restricted access to the database to accomplish various analysis tasks. The proposed engine (i) audits queries for trajectory data to block potential attacks to user privacy, (ii) supports range, distance, and k-nearest neighbors spatial and spatiotemporal queries, and (iii) preserves user anonymity in answers to queries by (a) augmenting the real trajectories with a set of carefully crafted, realistic fake trajectories, and (b) ensuring that no user-specific sensitive locations are reported as part of the returned trajectories.