Google today announced that it is open-sourcing its so-called differential privacy library, an internal tool the company uses to securely draw insights from datasets that contain the private and sensitive personal information of its users.
Differential privacy is a cryptographic approach to data science, particularly with regard to analysis, that allows someone relying on software-aided analysis to draw insights from massive datasets while protecting user privacy. It does so by mixing novel user data with artificial “white noise,” as explained by Wired’s Andy Greenberg.
