Authenticating Outsourced Location-based Skyline Queries under Shortest Path Distance
the University of Delaware
the Associate Director for Research of the Center for Cybersecurity, Assurance and Privacy (CCAP)
The rapid advance in cloud computing has made it increasingly popular for Location-based Service Providers (LBSPs) like Yelp to outsource their Points of Interest (POI) datasets to third-party Cloud Service Providers (CSPs), which in turn answer various data queries from mobile users on their behalf. A key security concern in such a system is that the CSPs cannot be fully trusted and may return forged and/or incorrect query results in favor of the POIs willing to pay. As an important type of query, location-based skyline queries (LBSQ) ask for the POIs that are not dominated by any other POI with respect to a certain query location. Despite several prior solutions for authenticating outsourced LBSQs, they can only support LBSQ under the Euclidean distance. How to authenticate outsourced LBSQs under the shortest path distance, which can better measure users' true travel distances in metropolitan areas, remains an open challenge. In this talk, I will first introduce a method for authenticating outsourced LBSQs over a single straight road segment under the Euclidean distance metric. I will then discuss how we can extend this method to authenticate LBSQs over general road networks under the shortest path distance.