NIST Finalizes Differential Privacy Rules to Protect Data

NIST finalized guidelines for evaluating differential privacy, a mathematical framework that obscures personally identifiable information in datasets while preserving statistical usefulness. This enables organizations to share data publicly while protecting sensitive information, even in the event of a data leak. The guidelines address data leak risks, security issues, and the importance of using proven techniques for differential privacy implementation.