Epsilon投票:差分隐私参数选择机制设计

Nitin Kohli, Paul Laskowski
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引用次数: 27

摘要

微分私有系统的行为由参数epsilon控制,该参数在保护个人隐私和返回准确结果之间建立了平衡。虽然系统所有者可以使用许多启发式方法来选择epsilon,但现有技术可能无法响应数据处于危险中的用户的需求。一个有希望的替代方案是允许用户表达他们对epsilon的偏好。在我们称为epsilon投票的系统中,用户将他们想要的参数值报告给选择器机制,该机制将它们聚合为单个值。我们应用机制设计的技术来询问这样的选择机制本身是否可以是真实的、私有的、匿名的,并且对用户也有响应。在不限制用户偏好的情况下,唯一可行的机制属于一类我们称之为带有幽灵的随机独裁。这是一个限制性类,其中最多有一个用户对所选的有任何影响。另一方面,当用户表现出单峰偏好时,更广泛的机制类别-概括中位数和其他顺序统计的机制-成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Epsilon Voting: Mechanism Design for Parameter Selection in Differential Privacy
The behavior of a differentially private system is governed by a parameter epsilon which sets a balance between protecting the privacy of individuals and returning accurate results. While a system owner may use a number of heuristics to select epsilon, existing techniques may be unresponsive to the needs of the users who's data is at risk. A promising alternative is to allow users to express their preferences for epsilon. In a system we call epsilon voting, users report the parameter values they want to a chooser mechanism, which aggregates them into a single value. We apply techniques from mechanism design to ask whether such a chooser mechanism can itself be truthful, private, anonymous, and also responsive to users. Without imposing restrictions on user preferences, the only feasible mechanisms belong to a class we call randomized dictatorships with phantoms. This is a restrictive class in which at most one user has any effect on the chosen epsilon. On the other hand, when users exhibit single-peaked preferences, a broader class of mechanisms - ones that generalize the median and other order statistics - becomes possible.
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