文章基本信息

标题：Improving the Similarity for Privacy in Location Based Service
本地全文：下载
作者：Reemah M. Alhebshi ; Jonathan Cazalas
期刊名称：International Journal of Computer and Information Technology
印刷版ISSN：2279-0764
出版年度：2014
卷号：3
期号：6
出版社：International Journal of Computer and Information Technology
摘要：With recent technological advancements in GPS- enabled devices, Location-Based Services (LBSs) have be effectively become a required commodity among users . Unfortunately, because LBS providers require users to report their location information, the issue of user privacy has become one of the foremost challe nges that researchers are delving time and resources into. Most existing approaches either can't fully protect user's location privacy, or can't provide accurate LBSs. The research being cond ucted in this sphere is aiming to mitigate the disparity that currently prevails between the protection of user information and the accuracy of that information. In our approach to resolve this issue, we are aiming to customize a previous work of Dewri [1]. In doing so, we are proposing to increase the granularity of similarity matrix and focus the new similarity matrix in a region near to the original point. In doing so, we hope to provide enhanced accuracy of locations, while allowing location anonymity for enhanced user privacy. Moreover, it will provide the users complete control and flexibility of their system bandwidth level.
关键词：component; Location-Based Services (LBSs); location ; privacy; security; location transformation; Quality of Service (QoS); ; similarity matrix