TY - GEN
T1 - LinkMirage
T2 - 23rd Annual Network and Distributed System Security Symposium, NDSS 2016
AU - Liu, Changchang
AU - Mittal, Prateek
N1 - Publisher Copyright:
© 2016 Internet Society.
PY - 2016
Y1 - 2016
N2 - Social relationships present a critical foundation for many real-world applications. However, both users and online social network (OSN) providers are hesitant to share social relationships with untrusted external applications due to privacy concerns. In this work, we design LinkMirage, a system that mediates privacy-preserving access to social relationships. LinkMirage takes users’ social relationship graph as an input, obfuscates the social graph topology, and provides untrusted external applications with an obfuscated view of the social relationship graph while preserving graph utility. Our key contributions are (1) a novel algorithm for obfuscating social relationship graph while preserving graph utility, (2) theoretical and experimental analysis of privacy and utility using real-world social network topologies, including a large-scale Google+ dataset with 940 million links. Our experimental results demonstrate that LinkMirage provides up to 10x improvement in privacy guarantees compared to the state-of-the-art approaches. Overall, LinkMirage enables the design of real-world applications such as recommendation systems, graph analytics, anonymous communications, and Sybil defenses while protecting the privacy of social relationships.
AB - Social relationships present a critical foundation for many real-world applications. However, both users and online social network (OSN) providers are hesitant to share social relationships with untrusted external applications due to privacy concerns. In this work, we design LinkMirage, a system that mediates privacy-preserving access to social relationships. LinkMirage takes users’ social relationship graph as an input, obfuscates the social graph topology, and provides untrusted external applications with an obfuscated view of the social relationship graph while preserving graph utility. Our key contributions are (1) a novel algorithm for obfuscating social relationship graph while preserving graph utility, (2) theoretical and experimental analysis of privacy and utility using real-world social network topologies, including a large-scale Google+ dataset with 940 million links. Our experimental results demonstrate that LinkMirage provides up to 10x improvement in privacy guarantees compared to the state-of-the-art approaches. Overall, LinkMirage enables the design of real-world applications such as recommendation systems, graph analytics, anonymous communications, and Sybil defenses while protecting the privacy of social relationships.
UR - http://www.scopus.com/inward/record.url?scp=85180751342&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85180751342&partnerID=8YFLogxK
U2 - 10.14722/ndss.2016.23277
DO - 10.14722/ndss.2016.23277
M3 - Conference contribution
AN - SCOPUS:85180751342
T3 - 23rd Annual Network and Distributed System Security Symposium, NDSS 2016
BT - 23rd Annual Network and Distributed System Security Symposium, NDSS 2016
PB - The Internet Society
Y2 - 21 February 2016 through 24 February 2016
ER -