Secure Collaborative Social Networks

被引:23
作者
Zhan, Justin [1 ]
机构
[1] Natl Ctr Protect Financial Infrastruct, Madison, SD 57042 USA
来源
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS | 2010年 / 40卷 / 06期
关键词
Privacy; security; social networks;
D O I
10.1109/TSMCC.2010.2050879
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A social network is the mapping and measuring of relationships and flows between individuals, groups, organizations, computers, websites, and other information/knowledge processing entities. The nodes in the network are the people and groups, while the links show relationships or flows between the nodes. Social networks provide both a visual and a mathematical analysis of relationships. Social network has been researched for a while. However, to our best knowledge, privacy-preserving social networks have not been well explored. In this paper, we would like to address how to build up a social network involving multiple parties. Data collection is a necessary step in the social-network-construction process. Due to privacy reasons, collecting data from different parties becomes difficult and these concerns may prevent the parties from directly sharing the data. How multiple parties collaboratively construct a social network without breaching data privacy presents a challenge. The objective of this paper is to provide a solution for privacy-preserving collaborative social-network problem.
引用
收藏
页码:682 / 689
页数:8
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