Practical Data-Oriented Microaggregation for Statistical Disclosure Control
IEEE Transactions on Knowledge and Data Engineering
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Robust and fast similarity search for moving object trajectories
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Ordinal, Continuous and Heterogeneous k-Anonymity Through Microaggregation
Data Mining and Knowledge Discovery
Preserving privacy in gps traces via uncertainty-aware path cloaking
Proceedings of the 14th ACM conference on Computer and communications security
Privacy Preservation in the Publication of Trajectories
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
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
Anonymizing moving objects: how to hide a MOB in a crowd?
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Towards Trajectory Anonymization: a Generalization-Based Approach
Transactions on Data Privacy
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
Discovering private trajectories using background information
Data & Knowledge Engineering
Hybrid microdata using microaggregation
Information Sciences: an International Journal
Movement Data Anonymity through Generalization
Transactions on Data Privacy
Privacy preservation in the dissemination of location data
ACM SIGKDD Explorations Newsletter
Information fusion in data privacy: A survey
Information Fusion
Microaggregation- and permutation-based anonymization of movement data
Information Sciences: an International Journal
Scalable mining of common routes in mobile communication network traffic data
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
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Huge amounts of movement data are automatically collected by technologies such as GPS, GSM, RFID, etc. Publishing such data is essential to improve transportation, to understand the dynamics of the economy in a region, etc. However, there are obvious threats to the privacy of individuals if their trajectories are published in a way which allows reidentification of the individual behind a trajectory. We contribute to the literature on privacy-preserving publication of trajectories by presenting: i) a distance measure for trajectories which naturally considers both spatial and temporal aspects of trajectories, is computable in polynomial time, and can cluster trajectories not defined over the same time span (something that previously proposed methods could not do); ii) a method to replace a cluster of trajectories by synthetic data that preserve all the visited locations and the number of original trajectories, among other features; iii) a comparison of our method with (k, δ)-anonymity [1] using trajectories generated by the Brinkhoff's generator [4] in the city of Oldenburg.