期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：3
出版社：S.S. Mishra
摘要：Social networking sites such as Facebook ,Google,twitter provide third party applications such as games and productivity applications by providing a social application platform. These interfaces enable popular site enhancements but poses privacy risks by exposing user data to third party developers. The current security mechanisms, such as privacy policies and access control mechanisms fall short on protecting the privacy of the users. In this paper, we are representing a framework for a privacy enhanced social network security application that technically enforces the protection of the personal data of a user, when interacting with social applications.Let us propose a multicriteria recommendation model that uses application based, category based, user based, and collaborative filtering mechanisms which are based on previous user decisions, and application requests to increase the privacy of the overall site's user population. Our project on the collected information indicate that the proposed framework enhanced the user security and privacy related to third -party application authorizations.
关键词：OAuth; Random number generation ;collaborative filtering; social networks; Prediction model
