Location Privacy in Pervasive Computing
IEEE Pervasive Computing
Achieving k-anonymity privacy protection using generalization and suppression
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Accuracy characterization for metropolitan-scale Wi-Fi localization
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Practical Lessons from Place Lab
IEEE Pervasive Computing
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
Discovering personally meaningful places: An interactive clustering approach
ACM Transactions on Information Systems (TOIS)
A Survey and Analysis of the P3P Protocol's Agents, Adoption, Maintenance, and Future
IEEE Transactions on Dependable and Secure Computing
End-user privacy in human-computer interaction
Foundations and Trends in Human-Computer Interaction
Communications of the ACM - Urban sensing: out of the woods
The election algorithm for semantically meaningful location-awareness
Proceedings of the 6th international conference on Mobile and ubiquitous multimedia
A conceptual view on trajectories
Data & Knowledge Engineering
Private queries in location based services: anonymizers are not necessary
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
P3P: Making Privacy Policies More Useful
IEEE Security and Privacy
Who's viewed you?: the impact of feedback in a mobile location-sharing application
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
On the tradeoff between privacy and utility in data publishing
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
A survey of computational location privacy
Personal and Ubiquitous Computing
Privacy in Location-Based Applications: Research Issues and Emerging Trends
Privacy in Location-Based Applications: Research Issues and Emerging Trends
Location Privacy Techniques in Client-Server Architectures
Privacy in Location-Based Applications
Discovering semantically meaningful places from pervasive RF-beacons
Proceedings of the 11th international conference on Ubiquitous computing
Casper*: Query processing for location services without compromising privacy
ACM Transactions on Database Systems (TODS)
Feeling-based location privacy protection for location-based services
Proceedings of the 16th ACM conference on Computer and communications security
Ground-Based Wireless Positioning
Ground-Based Wireless Positioning
The PROBE Framework for the Personalized Cloaking of Private Locations
Transactions on Data Privacy
Challenges and business models for mobile location-based services and advertising
Communications of the ACM
SeMiTri: a framework for semantic annotation of heterogeneous trajectories
Proceedings of the 14th International Conference on Extending Database Technology
Fine-Grained Cloaking of Sensitive Positions in Location-Sharing Applications
IEEE Pervasive Computing
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
A formal model of obfuscation and negotiation for location privacy
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Learning and recognizing the places we go
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Handling user-defined private contexts for location privacy in LBS
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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The advances in positioning technologies and the emergence of geolocation standards opens up to the development of innovative location-based services (LBS), e.g., web-based LBS. These services challenge existing privacy protection solutions. For example, the position information is provided by a third party, the location provider, and this party may be not fully trusted. In this paper, we analyze the web-based LBS model. Then we outline the privacy-aware geolocation strategy which minimizes the interaction with the untrusted location provider by caching the information that is useful to determine the position in proximity of the private positions, e.g., home, which have been already visited. The deployment of this strategy requires investigating several issues and novel tools. The objective of this paper is to discuss the technical challenges and suggest directions of research towards a comprehensive privacy-preserving framework. To our knowledge, this is the first work on privacy protection against untrusted location providers.