Differential privacy is a mathematical framework that limits how much an algorithm’s output can change when any one person’s record is added or removed. This guide explains the mechanism, trade-offs, evaluation, and controls that matter in practice.
Differential privacy is a mathematical framework that limits how much an algorithm’s output can change when any one person’s record is added or removed. This guide explains the mechanism, trade-offs, evaluation, and controls that matter in practice.