A Primer on Differential Privacy

Research report

Website/link: https://securelysharingdata.com/resources/vadhan.pdf

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Published date: January 1, 2019

Author: Salil Vadhan

Subject tag: Data Access | Privacy and data protection

Differential privacy is a strong, mathematical definition of privacy in the context of statistical and machine learning analysis. It is used to enable the collection, analysis, and sharing of a broad range of statistical estimates based on personal data, such as averages, contingency tables, and synthetic data, while protecting the privacy of the individuals in the data.
[This entry was sourced with minor edits from the Carnegie Endowment’s Partnership for Countering Influence Operations and its baseline datasets initiative. You can find more information here: https://ceip.knack.com/pcio-baseline-datasets]