Abstract
Recently, the widespread usage of smart phones and emergence of location based services (LBSs) have raised the necessity of data outsourcing paradigm. In this paradigm, a service provider (SP) offers services on the behalf of data owner (DO). However, the third party service provider may not be trustworthy. It may return incomplete or corrupted answers for personal benefits. Therefore, there must be a way to authenticate the answers returned by the SP. In this paper, we introduce an approach to authenticate an important class of LBSs, kNN queries in the obstructed space. A k nearest neighbor (kNN) query in the obstructed space enables a pedestrian to know k points of interest (POIs) such as restaurants or pharmacies that have k smallest distances from her current location considering the obstacles (e.g., buildings, lakes). Though authentication techniques of kNN queries exist for the Euclidean space and road networks, no work has been done to authenticate kNN queries in the obstructed space. We perform experiments using real datasets to show the effectiveness of our approach.
Published Version
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