A performance comparison of multi-hop wireless ad hoc network routing protocols
MobiCom '98 Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Achieving k-anonymity privacy protection using generalization and suppression
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Location Privacy in Mobile Systems: A Personalized Anonymization Model
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Real-Time Processing of Range-Monitoring Queries in Heterogeneous Mobile Databases
IEEE Transactions on Mobile Computing
MobiEyes: A Distributed Location Monitoring Service Using Moving Location Queries
IEEE Transactions on Mobile Computing
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
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
PAM: An Efficient and Privacy-Aware Monitoring Framework for Continuously Moving Objects
IEEE Transactions on Knowledge and Data Engineering
Processing generalized k-nearest neighbor queries on a wireless broadcast stream
Information Sciences: an International Journal
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This paper explores the problem of preserving location privacy in real-time location monitoring services. Because monitoring personal locations with untrusted service providers may breach monitored individuals' privacy, we adopt the system model that depends on a trusted anonymizer. The main role of the anonymizer is to blur individuals' locations into the cloaking regions for providing location k-anonymity to them. Most existing methods assume that the monitored individuals continually communicate with the anonymizer to report their current locations, and the anonymizer periodically regenerate their cloaking regions. However, this degrades the system performance due to the increased workload at the anonymizer as well as the severe communication bottleneck. With this problem in mind, we propose a distributed and cooperative privacy-preserving method, which leverages the computing capabilities of individuals' handheld devices in order to provide privacy guarantee (i.e., location k-anonymity) for the individuals in an efficient manner in terms of the workload at the anonymizer and the communication cost. The basic idea is to make the anonymizer and the individuals share the process of generating and keeping up-to-date cloaking regions. Through a series of simulations, we verify the efficiency of our work.