ConferenceIEEE International Conference on Computer Communications (INFOCOM) · 2019
Estimating frequencies of certain items among a
population is a basic step in data analytics, which enables more
advanced data analytics (e.g., heavy hitter identification, frequent
pattern mining), client software optimization, and detecting
unwanted or m ...
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Journal ArticleACM Transactions on Privacy and Security · February 28, 2018
We propose new privacy attacks to infer attributes (e.g., locations, occupations, and interests) of online social network users. Our attacks leverage seemingly innocent user information that is publicly available in online social netwo ...
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ConferenceUSENIX Security Symposium · 2018
Users in various web and mobile applications are vulnerable to attribute inference attacks, in which an attacker
leverages a machine learning classifier to infer a target
user’s private attributes (e.g., location, sexual orientation,
political view) from i ...
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Journal ArticleACM Transactions on Intelligent Systems and Technology · April 2014
The effects of social influence and homophily suggest that both network structure and node-attribute information should inform the tasks of link prediction and node-attribute inference. Recently, Yin et al. [2010a, 2010b] proposed an attribute-augm ...
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Journal ArticleProceedings of the National Academy of Sciences · January 31, 2012
The pigmentation patterns of shells in the genus
Conus
can be generated by a neural-network model of the mantle. We fit model parameters to the shell pigmentation patterns of 19 living ...
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ConferenceACM/USENIX Internet Measurement Conference (IMC) · 2012
Understanding social network structure and evolution has important implications for many aspects of network and system design
including provisioning, bootstrapping trust and reputation systems
via social networks, and defenses against Sybil attacks. Severa ...
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