ABSTRACT
The widespread adoption of location-based services (LBS) raises increasing concerns for the protection of personal location information. A common strategy, referred to as obfuscation, to protect location privacy is based on forwarding the LSB provider a coarse user location instead of the actual user location. Conventional approaches, based on such technique, are however based only on geometric methods and therefore are unable to assure privacy when the adversary is aware of the geographical context. This paper provides a comprehensive solution to this problem. Our solution presents a novel approach that obfuscates the user location by taking into account the geographical context and user's privacy preferences. We define several theoretical notions underlying our approach. We then propose a strategy for generating obfuscated spaces and an efficient algorithm which implements such a strategy. The paper includes several experimental results assessing performance, storage requirements and accuracy for the approach. The paper also discusses the system architecture and shows that the approach can be deployed also for clients running on small devices.
- M. Damiani, E. Bertino, and C. Silvestri. Protecting location privacy through semantics-aware obfuscation techniques. In Proc. of IFIPTM 2008, pages 231--245. Springer Boston, June 18--20 2008.Google ScholarCross Ref
- M. L. Damiani, E. Bertino, and C. Silvestri. PROBE: an obfuscation system for the protection of sensitive location information in lbs. CERIAS Technical Report, Purdue University, 2008.Google Scholar
- M. Duckham and L. Kulik. A formal model of obfuscation and negotiation for location privacy. In Pervasive Computing. Springer, 2005. Google ScholarDigital Library
- B. Gedik and L. Liu. Location privacy in mobile systems: A personalized anonymization model. In Proc. of the 25th IEEE ICDCS, 2005. Google ScholarDigital Library
- G. Ghinita, M. Damiani, E. Bertino, and C. Silvestri. Interactive Location Cloaking with the PROBE Obfuscator. In Proc. of the Tenth International Conference on Mobile Data Management: Systems, Services and Middleware, 2009. Google ScholarDigital Library
- G. Ghinita, P. Kalnis, A. Khoshgozaran, C. Shahabi, and K.-L.Tan. Private Queries in Location Based Services: Anonymizers are not Necessary. In Proc. ACM SIGMOD Conference, 2008. Google ScholarDigital Library
- M. Gruteser and D. Grunwald. Anonymous usage of location-based services through spatial and temporal cloaking. In Proc. of the 1st international conference on Mobile systems, applications and services. ACM Press, 2003. Google ScholarDigital Library
- U. Hengartner and P. Steenkiste. Access control to people location information. ACM Trans. Inf. Syst. Secur., 8(4):424--456, 2005. Google ScholarDigital Library
- P. Kalnis, G. Ghinita, K. Mouratidis, and D. Papadias. Preventing location-based identity inference in anonymous spatial queries. IEEE TKDE, 2007. Google ScholarDigital Library
- B. Krishnamachari, G. Ghinita, and P. Kalnis. Privacy-Preserving Publication of User Locations in the Proximity of Sensitive Sites. In Proc. SSDBM, 2008. Google ScholarDigital Library
- A. Machanavajjhala, J. Gehrke, D. Kifer, and M. Venkitasubramaniam. 1-Diversity: Privacy Beyond k-Anonymity. In Proc. ICDE, 2006. Google ScholarDigital Library
- M. F. Mokbel, C.-Y. Chow, and W. G. Aref. The new Casper: query processing for location services without compromising privacy. In Proc. VLDB, pages 763--774, 2006. Google ScholarDigital Library
- D. Moore. C Library Hilbert. c. http://www.caam.rice.edu/dougm.Google Scholar
- G. Myles, A. Friday, and N. Davies. Preserving privacy in environments with location-based applications. IEEE Pervasive Computing, 2(1):56--64, 2003. Google ScholarDigital Library
- Open GIS Consortium. Open GIS simple features specification for SQL, 1999. Revision 1.1.Google Scholar
- N. Poolsappasit and I. Ray. Towards Achieving Personalized Privacy for Location-Based Services. Transactions on Data Privacy, 2:1:77--99, 2009. Google ScholarDigital Library
- H. Samet. Foundations of Multidimensional and Metric data Structures. Morgan Kaufmann, 2006. Google ScholarDigital Library
- E. Snekkenes. Concepts for personal location privacy policies. In EC '01: Proceedings of the 3rd ACM conference on Electronic Commerce, pages 48--57, New York, NY, USA, 2001. ACM Press. Google ScholarDigital Library
- X. Xiao and Y. Tao. Personalized privacy preservation. In Proc. of the 2006 ACM SIGMOD, pages 229--240, New York, NY, USA, 2006. ACM. Google ScholarDigital Library
- P. H. Xue M., Kalnis P. Location Diversity: Enhanced Privacy Protection in Location Based Services. In Proc. of the International Symposium on Location and Context Awareness (LoCA), 2009. Google ScholarDigital Library
- M. L. Yiu, C. Jensen, X. Huang, and H. Lu. SpaceTwist: Managing the Trade-Offs Among Location Privacy, Query Performance, and Query Accuracy in Mobile Services. In proc. IEEE 24th International Conference on Data Engineering, 2008. Google ScholarDigital Library
- M. Youssef, V. Atluri, and N. R. Adam. Preserving mobile customer privacy: an access control system for moving objects and customer profiles. In Proc. MDM, 2005. Google ScholarDigital Library
Index Terms
Protecting location privacy against spatial inferences: the PROBE approach
Recommendations
Protecting location privacy: optimal strategy against localization attacks
CCS '12: Proceedings of the 2012 ACM conference on Computer and communications securityThe mainstream approach to protecting the location-privacy of mobile users in location-based services (LBSs) is to alter the users' actual locations in order to reduce the location information exposed to the service provider. The location obfuscation ...
Protecting location privacy using location semantics
KDD '11: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data miningAs the use of mobile devices increases, a location-based service (LBS) becomes increasingly popular because it provides more convenient context-aware services. However, LBS introduces problematic issues for location privacy due to the nature of the ...
Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms
Continued advances in mobile networks and positioning technologies have created a strong market push for location-based applications. Examples include location-aware emergency response, location-based advertisement, and location-based entertainment. An ...
Comments