Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Supporting anonymous location queries in mobile environments with privacygrid
Proceedings of the 17th international conference on World Wide Web
Privacy and location anonymization in location-based services
SIGSPATIAL Special
Extracting urban patterns from location-based social networks
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
A dummy-based anonymization method based on user trajectory with pauses
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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Due to the growing use of mobile devices, location-based services have become popular. A location service often requires the user's exact location to provide appropriate services and this brings the risk of threats to privacy. In this paper, we propose an anonymization method for users of location-based services in mobile environments. The anonymization approach is based on the well-known k-anonymity concept, but has additional features. We consider the situation that a mobile service (e.g., mobile advertisement) utilizes mobile users' profiles for its service. Since a profile contains privacy information such as the age and address of the user, the use of profile information brings another kind of privacy threat. The anonymization method proposed in this paper considers not only location information but also privacy-related attributes in the user's profile. The location anonymizer, a trusted third-party placed between users and mobile application services, anonymizes the location and profile attributes based on the request. We define a similarity measure between mobile users for anonymization purposes. The similarity is used for related users in terms of their locations and profile attributes. We present the concept behind our method and the anonymization algorithm, and then show some experimental results.