"Location" has  become a key differentiator in providing personalized services to end users. The rate of integration of location into various services and applications has been slower than expected. One of the primary reasons is the concern over user`s privacy . In location based services, a user has to reveal its exact location and request to the service provider. The service provider could reveal this information for monetary gains. Both, policy and technology changes are necessary to alleivate such concerns and to promote trust between the users and service providers.  Various models and algorithms have been proposed to protect users privacy. Much of the commercial location based services products resort to policy rather than technology solutions for protecting user privacy. Thus, there is still need to optimize current solutions and develop new and innovative solutions for widespread adoption for privacy enhancing technologies.

Our research on this topic heads in three main directions

1. Cache has been used in location based services to improve communication and computation cost. We are currently exploring the role of cache in enhancing privacy of the end users.
2. Currently, most privacy-aware algorithms and techniques in LBS are based on the k-anonymity concept. However, in certain scenarios, maintaining k-anonymity is not enough if the adversaries have more background knowledge. We are investigating some attacks that can make k-anonymity vulnerable, and designing new techniques to counter the attacks.
3. Most of the work in the literature assume a presence of a trusted third party (like a proxy) server that mediates the communication between the users and the service providers. So we are researching new models of interaction that seek to eliminate such trusted third party servers.

 Team Members:  Himanshu Pagey  (hpagey@cs.ucf.edu)

                                  Fuyu Liu ( liu@cs.ucf.edu)

Publications:         Various under submission.