Privacy leakage analysis in online social networks

被引:46
|
作者
Li, Yan [1 ]
Li, Yingjiu [1 ]
Yan, Qiang [1 ]
Deng, Robert H. [1 ]
机构
[1] Singapore Management Univ, Sch Informat Syst, Singapore 178902, Singapore
关键词
Online social network; Privacy control; Information flow; Private information leakage; Inherent exploit;
D O I
10.1016/j.cose.2014.10.012
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Online Social Networks (OSNs) have become one of the major platforms for social interactions, such as building up relationship, sharing personal experiences, and providing other services. The wide adoption of OSNs raises privacy concerns due to personal data shared online. Privacy control mechanisms have been deployed in popular OSNs for users to determine who can view their personal information. However, user's sensitive information could still be leaked even when privacy rules are properly configured. We investigate the effectiveness of privacy control mechanisms against privacy leakage from the perspective of information flow. Our analysis reveals that the existing privacy control mechanisms do not protect the flow of personal information effectively. By examining representative OSNs including Facebook, Google+, and Twitter, we discover a series of privacy exploits. We find that most of these exploits are inherent due to the conflicts between privacy control and OSN functionalities. The conflicts reveal that the effectiveness of privacy control may not be guaranteed as most OSN users expect. We provide remedies for OSN users to mitigate the risk of involuntary information leakage in OSNs. Finally, we discuss the costs and implications of resolving the privacy exploits. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:239 / 254
页数:16
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