Differential Privacy: The Pursuit of Protections by Default

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Abstract

First formalized in 2006, differential privacy is an approach based on a mathematically rigorous definition of privacy that allows formalization and proof of the guarantees against re-identification offered by a system. While differential privacy has been accepted by theorists for some time, its implementation has turned out to be subtle and tricky, with practical applications only now starting to become available. To date, differential privacy has been adopted by the U.S. Census Bureau, along with a number of technology companies, but what this means and how these organizations have implemented their systems remains a mystery to many.

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APA

Guevara, M., Desfontaines, D., Waldo, J., & Coatta, T. (2020, September 1). Differential Privacy: The Pursuit of Protections by Default. Queue. Association for Computing Machinery. https://doi.org/10.1145/3434571.3439229

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