Several courses are being offered that deal with new theories of data privacy, concerning how to usefully answer queries from a database while preserving the privacy of individuals in the database, even if the queries can be combined with auxiliary information from other data sources.
These concerns arise in response to the practical observation that even "anonymized" databases can often be "de-anonymized" by combining them with other information.
All the course sites below link to papers in the literature, and, at least at this early stage of development, there seems to be a great deal of consensus on which papers to cover.
The Algorithmic Foundations of Data Privacy taught by Aaron Roth this Fall at Penn
Algorithmic Challenges in Data Privacy taught at Penn State by Sofya Raskhodnikova and Adam D. Smith
Foundations of Privacy taught at Weizmann by Moni Naor.
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