A mathematical model for intimacy-based security protection in social network without violation of privacy Online publication date: Mon, 30-Mar-2020
by Hui Zheng; Jing He; Yanchun Zhang; Junfeng Wu; Zhenyan Ji
International Journal of High Performance Computing and Networking (IJHPCN), Vol. 15, No. 3/4, 2019
Abstract: Protection against spam, fraud and phishing becomes increasingly important in the applications of social networks. Online social network providers such as Facebook and MySpace collect data from users including their relation and education statuses. While these data are used to provide users with convenient services, improper use of these data such as spam advertisement can be annoying and even harmful. Even worse, if these data are somehow stolen or illegally gathered, the users might be exposed to fraud and phishing. To further protect individual privacy, we employ an intimacy algorithm without the violation of privacy. Also, we explore spammers through detecting unusual intimacy phenomenon. We, therefore, propose a mathematical model for intimacy-based security protection in a social network without the violation of privacy in this paper. Moreover, the feasibility and the effectiveness of our model is testified theoretically and experimentally.
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