Modeling k-anonymity framework for the proximity-based privacy protection in context-aware LBS

Abstract

With the development of Context-aware location based services, there is a large scope for user's access to preference based services. One of the main research areas in context-aware location based services is proximity-based privacy protection for the users. The objective of our approach to proximity-based privacy protection is to deviate from the implementation of the centralized anonymizer and model the k-anonymity framework as a secure gateway in the context aware location service provider. Our design of privacy-protection is principled on guaranteed privacy protection rather than assuming the anonymizer to be a trusted third-party providing privacy protection. Using a symbolic model checker tool NuSMV, proximity based privacy protection has been modeled through the k-anonymity framework and it is observed that the system takes care of all the constraints by satisfying most of the specifications. © 2011 Springer-Verlag.