PLASMA: personalized, location aware services over mobile architectures
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Shadow attacks on users' anonymity in pervasive computing environments
Pervasive and Mobile Computing
Towards Achieving Personalized Privacy for Location-Based Services
Transactions on Data Privacy
Privacy in location-based services: a system architecture perspective
SIGSPATIAL Special
Privately querying location-based services with SybilQuery
Proceedings of the 11th international conference on Ubiquitous computing
Distortion-based anonymity for continuous queries in location-based mobile services
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Understanding User Preferences and Awareness: Privacy Mechanisms in Location-Based Services
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part I
Anonymization of moving objects databases by clustering and perturbation
Information Systems
Trust no one: a decentralized matching service for privacy in location based services
Proceedings of the second ACM SIGCOMM workshop on Networking, systems, and applications on mobile handhelds
Enhancing WLAN location privacy using mobile behavior
Expert Systems with Applications: An International Journal
Optimized query forgery for private information retrieval
IEEE Transactions on Information Theory
Moving forward: location privacy and location awareness
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS
Air-Writing: a platform for scalable, privacy-preserving, spatial group messaging
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
History trajectory privacy-preserving through graph partition
Proceedings of the 1st international workshop on Mobile location-based service
Trajectory anonymity in publishing personal mobility data
ACM SIGKDD Explorations Newsletter
Cover locations: availing location-based services without revealing the location
Proceedings of the 10th annual ACM workshop on Privacy in the electronic society
A moving-object index for efficient query processing with peer-wise location privacy
Proceedings of the VLDB Endowment
SBNMA '11 Proceedings of the 2011 ACM workshop on Social and behavioural networked media access
Privacy-preserving assessment of location data trustworthiness
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Protecting User Privacy Better with Query l-Diversity
International Journal of Information Security and Privacy
Predictive spatio-temporal queries: a comprehensive survey and future directions
Proceedings of the First ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems
Preserving location privacy without exact locations in mobile services
Frontiers of Computer Science: Selected Publications from Chinese Universities
Geo-indistinguishability: differential privacy for location-based systems
Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
Protecting query privacy in location-based services
Geoinformatica
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Recently, highly accurate positioning devices enable us to provide various types of location-based services. On the other hand, because position data obtained by such devices include deeply personal information, protection of location privacy is one of the most significant issues of location-based services. Therefore, we propose a technique to anonymize position data. In our proposed technique, the psrsonal user of a location-based service generates several false position data (dummies) sent to the service provider with the true position data of the user. Because the service provider cannot distinguish the true position data, the user's location privacy is protected. We conducted performance study experiments on our proposed technique using practical trajectory data. As a result of the experiments, we observed that our proposed technique protects the location privacy of users.