Many privacy questions arise when collecting information about individuals: how to allow use of this data without compromising the privacy of the data subjects? How to ensure that the end users of this data can find useful answers to their queries? Various anonymization techniques have been proposed which aim to find meaningful tradeoffs between privacy and utility. This talk presents the background for privacy and anonymization. Then I'll describe methods for anonymizing social network data, represented as a large, sparse semantic graph, which is additionally challenging due to the complex patterns of interactions between individuals. I'll also discuss some unexpected connections to uncertain data management, which provides many further directions for future work.
This talk covers join work with Divesh Srivastava, Balachander Krishnamuthy, and Smriti Bhagat.
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