In an era when data is everything, everywhere, all at once and computation has almost no limit, ensuring privacy while leveraging data analytics is paramount. The US Department of Commerce’s National ...

Traditionally, companies have relied upon data masking, sometimes called de-identification, to protect data privacy. The basic idea is to remove all personally identifiable information (PII) from each ...

Alexandra Wood, Micah Altman, Kobbi Nissim, and Salil Vadhan—collaborators with the Privacy Tools project—published a chapter in the Handbook on Using ...

In a world increasingly dominated by data, privacy has become both a precious commodity and a pressing concern. Enter differential privacy to protect individuals’ data in an era where information, ...

Google today released an open-source version of the differential privacy library it uses to power some of its own core products. Developers will be able to take this library and build their own tools ...

On Friday, Google debuted a new product developed with OpenMined that allows any Python developer to process data with differential privacy. The two have been working on the project for a year, and ...

Hiding sensitive data in a sea of noise might have more value than encryption in some use cases. Here are the most likely differential privacy applications and their trade-offs. In the past, the ...