Authentication of Multiple-User Spatial Keywords Queries
Isaac Amankona Obiri, Yong Wang, Raphael Elimeli Nuhoho, Erick Owiyo · 2018
A top-k Multiple-user Spatial Keywords (MUSK) query takes a location and a set of keywords as arguments and returns the k best point of interests (POIs) that satisfy multiple-user's happiness. In the database outsourcing paradigm, data owner (DO) delegates the role of answering user's queries to a cloud service provider(CSP). Since either the CSP or an intruder can falsify the query results, there is the need for the users to authenticate their query results. Therefore, in this paper we design some algorithms and introduce new data structure MIL-Quadtree, to efficiently process MUSK query on road network. Comprehensive experiments were carried out on real datasets to show the effectiveness and scalability of the proposed framework under various parameter settings.