Outsourcing Search Services on Private Spatial Data

Social networking and content sharing service providers, e.g., Facebook and Google Maps, enable their users to upload and share a variety of user-generated content, including location data such as points of interest. Users wish to share location data through an (untrusted) service provider such that trusted friends can perform spatial queries on the data. We solve the problem by transforming the location data before uploading them. We contribute spatial transformations that re-distribute locations in space and a transformation that employs cryptographic techniques. The data owner selects transformation keys and shares them with the trusted friends. Without the keys, it is infeasible for an attacker to reconstruct the exact original data points from the transformed points. These transformations achieve different tradeoffs between query efficiency and data security. In addition, we describe an attack model for studying the security properties of the transformations. Empirical studies suggest that the proposed methods are secure and efficient.