Secure ranked query processing in location based services accessing outsourced spatial databases

This paper introduce a geographic information is present on the internet which is in the scattered format. When user search for any place then various locations based service providers find out the results. The commonly used location based service providers are Google, Bing, Yahoo etc. we considers a novel distributed system for collaborative location-based information generation and sharing which become increasingly popular due to the explosive growth of Internet-capable and location-aware mobile devices. The results that are given by location based service providers not fully processed. The system consists of a data collector, data contributors, location-based service providers (LBSPs), and system users. The data collector gathers reviews about points-of-interest (POIs) from data contributors, while LBSPs purchase POI data sets from the data collector and allow users to perform spatial top-k queries which ask for the POIs in a certain region and with the highest k ratings for an interested POI attribute. The data contributor is the peoples or users who provide the information about the place. The user can gives comment and reviews to the product or the place. It's not necessary the LBSP provides proper information. In practice, LBSPs are untrusted and may return fake query results for various bad motives, e.g., in favour of POIs willing to pay. In our approach when the data contributor searches for any query, it will process by the LBSP. But before result showing to the user, it will process by the data collector. There are various results for the same query. So each query processed and special top result according to the location will provide to the users. This paper presents three novel schemes for users to detect fake spatial snapshot and moving top-k query results as an effort to foster the practical deployment and use of the proposed system.