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  1. Ligett, Katrina ; Gupta, Swati (Ed.)
    We give the first closed-form privacy guarantees for the Generalized Gaussian mechanism (the mechanism that adds noise x to a vector with probability proportional to exp(-(||x||_p/Īƒ)^p) for some Īƒ, p), in the setting of answering k counting (i.e. sensitivity-1) queries about a database with (Îĩ, δ)-differential privacy (in particular, with low 𝓁_∞-error). Just using Generalized Gaussian noise, we obtain a mechanism such that if the true answers to the queries are the vector d, the mechanism outputs answers dĖƒ with the 𝓁_∞-error guarantee: đ”ŧ[||dĖƒ - d||_∞] = O(√{k log log k log(1/δ)}/Îĩ). This matches the error bound of [Steinke and Ullman, 2017], but using a much simpler mechanism. By composing this mechanism with the sparse vector mechanism (generalizing a technique of [Steinke and Ullman, 2017]), we obtain a mechanism improving the √{k log log k} dependence on k to √{k log log log k}, Our main technical contribution is showing that certain powers of Generalized Gaussians, which follow a Generalized Gamma distribution, are sub-gamma. In subsequent work, the optimal 𝓁_∞-error bound of O(√{k log (1/δ)}/Îĩ) has been achieved by [Yuval Dagan and Gil Kur, 2020] and [Badih Ghazi et al., 2020] independently. However, the Generalized Gaussian mechanism has some qualitativemore »advantages over the mechanisms used in these papers which may make it of interest to both practitioners and theoreticians, both in the setting of answering counting queries and more generally.« less
  2. Ligett, Katrina ; Gupta, Swati (Ed.)
    The 2020 Decennial Census will be released with a new disclosure avoidance system in place, putting differential privacy in the spotlight for a wide range of data users. We consider several key applications of Census data in redistricting, developing tools and demonstrations for practitioners who are concerned about the impacts of this new noising algorithm called TopDown. Based on a close look at reconstructed Texas data, we find reassuring evidence that TopDown will not threaten the ability to produce districts with tolerable population balance or to detect signals of racial polarization for Voting Rights Act enforcement.