SoK：差分隐私
SoK: Differential Privacies
摘要：
在2006年首次引入后不久，差分隐私成为旗舰数据隐私定义。从那时起，提出了许多变体和扩展，以适应不同的场景和攻击者模型。在这项工作中，我们提出了一个系统的分类这些变种和扩展。我们列出了所有基于差分隐私的数据隐私定义，并根据原始定义的哪个方面被修改，将其分为七类。这些类别的作用类似于维度：同一类别的变体不能组合，但不同类别的变体可以组合形成新的定义。我们还建立了这些概念之间的相对强度的偏序总结现有的结果。此外，我们列出了这些定义满足一些理想的属性，如组合，后处理，凸性提供一个新的证明或收集现有的。
英文摘要：
Shortly after it was first introduced in 2006, differential privacy became the flagship data privacy definition. Since then, numerous variants and extensions were proposed to adapt it to different scenarios and attacker models. In this work, we propose a systematic taxonomy of these variants and extensions. We list all data privacy definitions based on differential privacy, and partition them into seven categories, depending on which aspect of the original definition is modified. These categories act like dimensions: variants from the same category cannot be combined, but variants from different categories can be combined to form new definitions. We also establish a partial ordering of relative strength between these notions by summarizing existing results. Furthermore, we list which of these definitions satisfy some desirable properties, like composition, post-processing, and convexity by either providing a novel proof or collecting existing ones.
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