On location models for ubiquitous computing
Personal and Ubiquitous Computing
Location Privacy in Mobile Systems: A Personalized Anonymization Model
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
Preventing Location-Based Identity Inference in Anonymous Spatial Queries
IEEE Transactions on Knowledge and Data Engineering
Applying hierarchical graphs to pedestrian indoor navigation
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Indoor Space: A New Notion of Space
W2GIS '08 Proceedings of the 8th International Symposium on Web and Wireless Geographical Information Systems
Location Diversity: Enhanced Privacy Protection in Location Based Services
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Constructing Hierarchical Representations of Indoor Spaces
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Towards an Indoor Level-of-Detail Model for Route Visualization
MDM '09 Proceedings of the 2009 Tenth International Conference on Mobile Data Management: Systems, Services and Middleware
Providing K-Anonymity in location based services
ACM SIGKDD Explorations Newsletter
Geo-coding scheme for multimedia in indoor space
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Due to complex structure of indoor space, the demand on LBS (Location Based Services) in indoor space has been increasing as well as outdoor. Although LBS give convenience for users, they still have problems of exposing personal location and privacy. In order to protect privacy, many researches have been done, among which location K-anonymity is a method by cloaking locations through ASR (Anonymizing Spatial Region) involving K-1 other users. However there is a limitation of this method to apply in indoor space that it assumes Euclidean Space and indoor space is characterized as non-Euclidean space in most cases unlike outdoor space. In this paper, we propose a new approach to location K-anonymity in indoor space. Our approach is based on the hierarchical structure of indoor space. First, we propose several algorithms to construct hierarchical structures for a given indoor space. Second, we introduce ASR generation algorithms to ensure the location K-anonymity with hierarchical structures. We analyze our methods through experimental analysis.