The demands to make data available are growing ever louder, including open data initiatives and "data monetization". But the problem of doing so without disclosing confidential information is a subtle and difficult one. Is "private data release" an oxymoron? This paper (accompanying an invited talk) aims to delve into the motivations of data release, explore the challenges, and outline some of the current statistical approaches developed in response to this confounding problem.
@InProceedings{cormode:LIPIcs.ICDT.2015.1, author = {Cormode, Graham}, title = {{The Confounding Problem of Private Data Release}}, booktitle = {18th International Conference on Database Theory (ICDT 2015)}, pages = {1--12}, series = {Leibniz International Proceedings in Informatics (LIPIcs)}, ISBN = {978-3-939897-79-8}, ISSN = {1868-8969}, year = {2015}, volume = {31}, editor = {Arenas, Marcelo and Ugarte, Mart{\'\i}n}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICDT.2015.1}, URN = {urn:nbn:de:0030-drops-49977}, doi = {10.4230/LIPIcs.ICDT.2015.1}, annote = {Keywords: privacy, anonymization, data release} }
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