Title: A mathematical model for intimacy-based security protection in social network without violation of privacy

Authors: Hui Zheng; Jing He; Yanchun Zhang; Junfeng Wu; Zhenyan Ji

Addresses: University of Chinese Academy of Sciences, Beijing, China; Victoria University, Ballarat Rd, Footscray VIC 3011, Melbourne, Australia; Fudan University, 220 Handan Rd, WuJiaoChang, Yangpu Qu, Shanghai Shi, 200433, China ' Institute of Information Technology, Nanjing University of Finance and Economics, Nanjing, China; School of Software and Electrical Engineering, Swinburne University of Technology, John St, Hawthorn VIC 3122, Melbourne, Australia ' Centre for Applied Informatics, College of Engineering and Science, Victoria University, Ballarat Rd, Footscray VIC 3011, Melbourne, Australia; Fudan University, Shanghai, China ' Sun Yat-sen University, Guangzhou, Guangdong, China ' Institute of Software Engineering, Beijing Jiaotong University, Beijing, China

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.

Keywords: social network; privacy protection; intimacy; spam detection.

DOI: 10.1504/IJHPCN.2019.106084

International Journal of High Performance Computing and Networking, 2019 Vol.15 No.3/4, pp.121 - 132

Received: 12 Nov 2017
Accepted: 27 Apr 2018
Published online: 30 Mar 2020 *

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