Location Privacy in Mobile Systems: A Personalized Anonymization Model
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To benefit from a location-based service, a person must reveal her location to the service. However, knowing the person's location might allow the service to re-identify the person. Location privacy based on k-anonymity addresses this threat by cloaking the person's location such that there are at least k-1 other people within the cloaked area. We propose a distributed approach that integrates nicely with existing infrastructures for location-based services, as opposed to previous work. Our approach is based on homomorphic encryption and has several organizations, such as operators of cellphone networks, collaborate to let a user learn whether k-anonymity holds for her area without the organizations learning any additional information. We also outline several challenges that remain to be addressed.