Query and update efficient B+-tree based indexing of moving objects
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
The Bdual-Tree: indexing moving objects by space filling curves in the dual space
The VLDB Journal — The International Journal on Very Large Data Bases
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
Location Privacy in Moving-Object Environments
Transactions on Data Privacy
Bob-tree: an efficient B+-tree based index structure for geographic-aware obfuscation
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part I
A moving-object index for efficient query processing with peer-wise location privacy
Proceedings of the VLDB Endowment
An open design privacy-enhancing platform supporting location-based applications
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
A Hilbert-based framework for preserving privacy in location-based services
International Journal of Intelligent Information and Database Systems
ICT-EurAsia'13 Proceedings of the 2013 international conference on Information and Communication Technology
Semantic-Aware obfuscation for location privacy at database level
ICT-EurAsia'13 Proceedings of the 2013 international conference on Information and Communication Technology
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The next generation of location-based services has been being predicted to achieve its superior development over the coming years. Keeping pace with this growth are new trends of predictive applications emerging to meet the demands of end-users and satisfy their matters of life. The violation of users' private information from their position disclosure, however, cuts off their beliefs when they enjoy such services. In this paper, therefore, we propose a novel index structure known as PPST-tree, which is able to deal with predictive and aggregate queries and is aware of trajectory privacy protection towards future positions of moving objects. Moreover, the prediction model and related strategies are also introduced in order to support location-based applications whereas user privacy is still preserved. Last but not least, privacy analyses and performance experiments show how well the proposed method can help.