A Unified Interpretation of the Gaussian Mechanism for Differential Privacy Through the Sensitivity Index - Kaissis, Georgios; Knolle, Moritz; Jungmann, Friederike; Ziller, Alexander; Usynin, Dmitrii; Rueckert, Daniel (Journal of Privacy and Confidentiality, 2022)
The Gaussian mechanism (GM) represents a universally employed tool for achieving differential privacy (DP), and a large body of work has been devoted to its analysis. We argue that the three prevailing interpretations of the GM, namely epsilon/delta-DP, f-DP and Rényi DP can be expressed by using a single parameter psi, which we term the sensitivity index. Psi uniquely characterises the GM and its properties by encapsulating its two fundamental quantities: the sensitivity of the query and the magnitude of the noise perturbation. With strong links to the ROC curve and the hypothesis-testing interpretation of DP, psi offers the practitioner a powerful method for interpreting, comparing and communicating the privacy guarantees of Gaussian mechanisms.