De-anonymizing Social Networks

被引：647

作者：

Narayanan, Arvind ^{[1
]}

Shmatikov, Vitaly ^{[1
]}

机构：

[1] Univ Texas Austin, Austin, TX 78712 USA

来源：

PROCEEDINGS OF THE 2009 30TH IEEE SYMPOSIUM ON SECURITY AND PRIVACY | 2009年

基金：

美国国家科学基金会;

关键词：

TIES;

D O I：

10.1109/SP.2009.22

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Operators of online social networks are increasingly sharing potentially sensitive information about users and their relationships with advertisers, application developers, and data-mining researchers. Privacy is typically protected by anonymization, i.e., removing names, addresses, etc. We present a framework for analyzing privacy and anonymity in social networks and develop a new re-identification algorithm targeting anonymized social-network graphs. To demonstrate its effectiveness on real-world networks, we show that a third of the users who can be verified to have accounts on both Twitter a popular microblogging service, and Flickr an online photo-sharing site, can be re-identified in the anonymous Twitter graph with only a 12% error rate. Our de-anonymization algorithm is based purely on the network topology, does not require creation of a large number of dummy "sybil" nodes, is robust to noise and all existing defenses, and works even when the overlap between the target network and the adversary's auxiliary information is small.

引用

页码：173 / 187

页数：15