EPPD: Efficient and privacy-preserving proximity testing with differential privacy techniques

摘要

With the ubiquity of mobile devices, location-based social networking applications have been widely used in people's daily life. However, due to the importance and sensitivity of location information, these applications may lead to serious security issues for user's location privacy. To handle these location privacy challenges, in this paper, we propose an efficient and privacy-preserving proximity testing scheme, called EPPD, for location-based services. With EPPD, a group of users can test whether they are within a given distance with minimal privacy disclosure. In specific, EPPD is comprised of two phases: first, users periodically upload their encrypted locations to service provider; and later, users can send requests to service provider for proximity testing and obtain the final testing results. Detailed security analysis shows that EPPD can achieve privacy-preserving proximity testing. In addition, performance evaluations via extensive simulations also demonstrate the efficiency and effectiveness of EPPD in term of low computational cost and communication overhead.