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 $(\epsilon ,\delta )$-differential privacy (DP) guarantees when releasing the result of a query or function $f(\cdot)\i…