Open Access

ARTICLE

Personalized Privacy Protecting Model in Mobile Social Network

Pingshui Wang^1,*, Zecheng Wang¹, Tao Chen^1,2, Qinjuan Ma¹

1 Anhui University of Finance and Economics, Bengbu, 233030, China.
2 University of Kansas, Lawrence, Kansas, 66045, USA.

* Corresponding Author: Pingshui Wang. Email: .

Computers, Materials & Continua 2019, 59(2), 533-546. https://doi.org/10.32604/cmc.2019.05570

Abstract

With the rapid development of the new generation of information technology, the analysis of mobile social network big data is getting deeper and deeper. At the same time, the risk of privacy disclosure in social network is also very obvious. In this paper, we summarize the main access control model in mobile social network, analyze their contribution and point out their disadvantages. On this basis, a practical privacy policy is defined through authorization model supporting personalized privacy preferences. Experiments have been conducted on synthetic data sets. The result shows that the proposed privacy protecting model could improve the security of the mobile social network while keeping high execution efficiency

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Keywords

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Citations