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Differential Privacy: A Primer For A Non-Technical Audience, Alexandra Wood, Micah Altman, Aaron Bembenek, Mark Bun, Marco Gaboardi, James Honaker, Kobbi Nissim, David R. O'Brien, Thomas Steinke, Salil Vadhan
Differential Privacy: A Primer For A Non-Technical Audience, Alexandra Wood, Micah Altman, Aaron Bembenek, Mark Bun, Marco Gaboardi, James Honaker, Kobbi Nissim, David R. O'Brien, Thomas Steinke, Salil Vadhan
Vanderbilt Journal of Entertainment & Technology Law
Differential privacy is a formal mathematical framework for quantifying and managing privacy risks. It provides provable privacy protection against a wide range of potential attacks, including those currently unforeseen. Differential privacy is primarily studied in the context of the collection, analysis, and release of aggregate statistics. These range from simple statistical estimations, such as averages, to machine learning. Tools for differentially private analysis are now in early stages of implementation and use across a variety of academic,industry, and government settings. Interest in the concept is growing among potential users of the tools, as well as within legal and policy communities, …
Fool's Gold: An Illustrated Critique Of Differential Privacy, Jane Bambauer, Krishnamurty Muralidhar, Rathindra Sarathy
Fool's Gold: An Illustrated Critique Of Differential Privacy, Jane Bambauer, Krishnamurty Muralidhar, Rathindra Sarathy
Vanderbilt Journal of Entertainment & Technology Law
Differential privacy has taken the privacy community by storm. Computer scientists developed this technique to allow researchers to submit queries to databases without being able to glean sensitive information about the individuals described in the data. Legal scholars champion differential privacy as a practical solution to the competing interests in research and confidentiality, and policymakers are poised to adopt it as the gold standard for data privacy. It would be a disastrous mistake. This Article provides an illustrated guide to the virtues and pitfalls of differential privacy. While the technique is suitable for a narrow set of research uses, the …