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20112023
most citedAnalyzing Federated Learning through an Adversarial Lens

382 citations · 2.5k across the 96 of their papers we have counts for

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5 papers · 1 filter

cs.SI2018

Blind De-anonymization Attacks using Social Networks

Wei-Han Lee, Changchang Liu, Shouling Ji +2

It is important to study the risks of publishing privacy-sensitive data. Even if sensitive identities (e.g., name, social security number) were removed and advanced data perturbati…

cs.SI2017

Quantification of De-anonymization Risks in Social Networks

Wei-Han Lee, Changchang Liu, Shouling Ji +2

The risks of publishing privacy-sensitive data have received considerable attention recently. Several de-anonymization attacks have been proposed to re-identify individuals even if…

cs.SI2015★ 43 cited

SybilFrame: A Defense-in-Depth Framework for Structure-Based Sybil Detection

Peng Gao, Neil Zhenqiang Gong, Sanjeev Kulkarni +2

Sybil attacks are becoming increasingly widespread, and pose a significant threat to online social systems; a single adversary can inject multiple colluding identities in the syste…

cs.SI2015★ 6 cited

LinkMirage: How to Anonymize Links in Dynamic Social Systems

Changhchang Liu, Prateek Mittal

Social network based trust relationships present a critical foundation for designing trustworthy systems, such as Sybil defenses, secure routing, and anonymous/censorshipresilient…

cs.SI2012★ 42 cited

Evolution of Social-Attribute Networks: Measurements, Modeling, and Implications using Google+

Neil Zhenqiang Gong, Wenchang Xu, Ling Huang +4

Understanding social network structure and evolution has important implications for many aspects of network and system design including provisioning, bootstrapping trust and reputa…