Data and Structural k-Anonymity in Social Networks

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Dependence Makes You Vulnberable: Differential Privacy Under Dependent Tuples (2016, background): “Data privacy is an issue of critical importance, motivating perturbation of query results over sensitive datasets for protecting users’ privacy [5], [12], [26], [29], [31], [38].”
"On the internet, nobody knows you're a dog": a twitter case study of anonymity in social networks (2014, background): “While some researchers have been trying to improve the anonymity guarantees in a social network [40, 7], there is a large body of research work on deanonymizing users and linking users across different social networks.”