文章基本信息

标题：A Frame Work for Preserving Privacy in Social Media using Generalized Gaussian Mixture Model
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作者：P Anuradha ; Y.Srinivas ; MHM Krishna Prasad 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2015
卷号：6
期号：7
DOI：10.14569/IJACSA.2015.060711
出版社：Science and Information Society (SAI)
摘要：Social networking sites helps in developing virtual communities for people to share their thoughts, interest activities or to increase their horizon of camaraderie. Social networking sites come under few of the most frequently browsed categories websites in the world. Nevertheless Social Networking sites are also vulnerable to various problems, threats and attacks such as disclosure of information, identity thefts etc. Privacy practice in social networking sites often come into sight, as information sharing stands in conflict with the disclosure-related misuse. Face book is one such most popular and widely used Social Networking sites which have its own robust set of Privacy mechanisms. Yet they are also prone to various privacy issues and attacks. The impulse in this paper lies in proposing a novel approach for improving the privacy among the social networking sites .The article presents the issues by a novel approach based on tagging and a model based technique based on generalized Gaussian Mixture Model.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; Privacy; Social Network; Social Relevant Groups; Generalized GMM; Tagging