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Is the Privacy of Network Data an Oxymoron?

Statisticians and computer scientists have yet to deal with privacy protection for large-scale sparse statistical databases in an adequate and systematic fashion, especially those associated with social networks. I will review some of the traditional approaches to disclosure limitation used for more standard rectangular n by p data arrays and discuss them from the perspective of usability (freedom from systematic distortions), transparency (the provision of information bias and variability), and duality (balancing the risk-utility trade-off). Then I will explain why extensions of these approaches to the domain of network data pose even greater challenges and review progress on the topic to date.