DocumentCode
1805167
Title
Grouping friends to improve privacy on Social Networking Sites
Author
Chaochen Qian ; Xiaochun Xiao ; Siming Chen ; Xueping Wang
Author_Institution
School of Computer Science, Fudan University, Shanghai Key Laboratory of Integrate Administration Technologies for Information Security, 220 Handan Road, 200433 China
fYear
2013
fDate
1-8 Jan. 2013
Firstpage
1
Lastpage
6
Abstract
Social Networking Sites (SNS) such as Facebook and MySpace have attracted millions of users because of their ability to combine individuals by social graphs. Nonetheless, considerable amount of users are suffering from their poor privacy settings. It is partly due to their lack of the awareness of privacy. To most normal users, the too exhausting privacy settings on SNS is another important reason. Moreover, even friends cannot be trusted all the time, and the privacy issues involving friends have actually been serious. In this paper1, we propose a novel approach of grouping friends to improve the privacy policy. We introduce a closeness degree model to quantify relationship between one user and his friends, based on which all the friends can be categorized automatically and dynamically. With some further statistical inference and analysis, our approach reflects the users´ tendency of disclosing personal data as well as their original privacy preferences.
Keywords
Blogs; Computational modeling; Data privacy; Databases; History; Mathematical model; Privacy; SNS; grouping friends; privacy;
fLanguage
English
Publisher
ieee
Conference_Titel
Conference Anthology, IEEE
Conference_Location
China
Type
conf
DOI
10.1109/ANTHOLOGY.2013.6784955
Filename
6784955
Link To Document