Privacy Loss of Noise Perturbation via Concentration Analysis of A Product Measure

Shuainan Liu, Tianxi Ji, Zhongshuo Fang +2

Noise perturbation is one of the most fundamental approaches for achieving $(\hat{I}\mu ,\hat{I}´)$-differential privacy (DP) guarantees when releasing the result of a query or function $f(\cdot)…