What is Differential Privacy?

Differential privacy is a privacy-preserving technique that adds statistical noise to datasets, ensuring individual data points cannot be reverse-engineered while still allowing meaningful analysis. It is widely used in AI, data analytics, and government data-sharing initiatives to protect sensitive information while maintaining utility.