论文标题
差异隐私中的后处理的偏见和差异
Bias and Variance of Post-processing in Differential Privacy
论文作者
论文摘要
后处理免疫是具有差异隐私的基本属性：它可以将任意数据独立的转换应用于差异私人输出的结果而不会影响其隐私保证。当查询输出必须满足域约束时，可以使用后处理将隐私的输出投影到可行的区域。此外，当可行的区域是凸面时，一类广泛采用的后处理步骤也可以确保提高准确性。后处理已成功应用于许多应用程序，包括人口普查数据释放，能源系统和移动性。但是，它对噪声分布的影响尚不清楚：经常认为后处理可能引入偏见并增加差异。本文朝着了解后处理的特性迈出了第一步。它考虑了人口普查数据的发布，并在理论上和经验上都研究了广泛采用的后处理功能的行为。
Post-processing immunity is a fundamental property of differential privacy: it enables the application of arbitrary data-independent transformations to the results of differentially private outputs without affecting their privacy guarantees. When query outputs must satisfy domain constraints, post-processing can be used to project the privacy-preserving outputs onto the feasible region. Moreover, when the feasible region is convex, a widely adopted class of post-processing steps is also guaranteed to improve accuracy. Post-processing has been applied successfully in many applications including census data-release, energy systems, and mobility. However, its effects on the noise distribution is poorly understood: It is often argued that post-processing may introduce bias and increase variance. This paper takes a first step towards understanding the properties of post-processing. It considers the release of census data and examines, both theoretically and empirically, the behavior of a widely adopted class of post-processing functions.
