期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2016
卷号：4
期号：3
页码：3583
DOI：10.15680/IJIRCCE.2016.0403155
出版社：S&S Publications
摘要：Location based system are used for finding out point of interests (POI) from a specific location. Usually a GPS latitude and longit ude is sent as an input to the location servers and based on the GPS coordinate the point of interests can be served back to the client from the location server. In the project we proposed to solve problems associated with the location data. The user does not want to send his location data (GPS coordinate) to the server directly, since doing so the server can find the user's location preferences and use that data for advertising the user's privacy is lost. The second part is like the server wants to protect its data from the user query. The server want to return back only relevant data to the user .The server cannot sent back other sensitive data to the user. We propose a major enhancement upon previous solutions by introducing a two stage approach, where th e first step is based on Enhanced Symmetric key Transfer and the second step is based on Private Information based on Enhanced Symmetric key Retrieval, to achieve a secure solution for both parties. The solution we present is efficient and practical in man y scenarios. We implement the solution using a real cloud location server and android mobile application. . (1) The system only requires a semi - trusted third party, responsible for carrying out simple matching operations correctly. This semi - trusted third party does not have any information about a user's location. (2) Secure snapshot and continuous location privacy is guaranteed under our defined adversary models. (3) The communication cost for the user does not depend on the user's desired privacy level; it only depends on the number of relevant points of interest in the vicinity of the user. (4) Although we only focus on range and k - nearest - neighbor queries in this work, our system can be easily extended to support other spatial queries without changing t he algorithms run by the semi - trusted third party and the database server, provided the required search area of a spatial query can be abstracted into spatial regions. Experimental results show that our DGS is more efficient than the state - of - the - art priva cy - preserving technique for continuous LBS
