Congenial Differential Privacy under Mandated Disclosure

Ruobin Gong, X. Meng
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引用次数: 22

Abstract

Differentially private data releases are often required to satisfy a set of external constraints that reflect the legal, ethical, and logical mandates to which the data curator is obligated. The enforcement of constraints, when treated as post-processing, adds an extra phase in the production of privatized data. It is well understood in the theory of multi-phase processing that congeniality, a form of procedural compatibility between phases, is a prerequisite for the end users to straightforwardly obtain statistically valid results. Congenial differential privacy is theoretically principled, which facilitates transparency and intelligibility of the mechanism that would otherwise be undermined by ad-hoc post-processing procedures. We advocate for the systematic integration of mandated disclosure into the design of the privacy mechanism via standard probabilistic conditioning on the invariant margins. Conditioning automatically renders congeniality because any extra post-processing phase becomes unnecessary. We provide both initial theoretical guarantees and a Markov chain algorithm for our proposal. We also discuss intriguing theoretical issues that arise in comparing congenital differential privacy and optimization-based post-processing, as well as directions for further research.
强制披露下的同类差异隐私
不同的私有数据发布通常需要满足一组外部约束,这些约束反映了数据管理员必须遵守的法律、道德和逻辑要求。约束的实施,当被视为后处理时,在私有数据的生产中增加了一个额外的阶段。在多阶段处理理论中,人们很好地理解了相合性,即阶段之间的一种程序相容性,是最终用户直接获得统计有效结果的先决条件。相宜的差别隐私在理论上是有原则的,它促进了机制的透明度和可理解性,否则就会被特别的后处理程序所破坏。我们主张通过在不变边际上的标准概率条件,将强制披露系统地整合到隐私机制的设计中。条件反射自动呈现亲和性,因为任何额外的后处理阶段都变得不必要。我们为我们的建议提供了初始理论保证和马尔可夫链算法。我们还讨论了在比较先天差异隐私和基于优化的后处理时出现的有趣的理论问题,以及进一步研究的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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