中央研究院 資訊科學研究所

活動訊息

友善列印

學術演講

How Private Are Commonly-Used Voting Rules?

  • 呂昀 小姐 (蘇格蘭愛丁堡大學)
    邀請人:鐘楷閔
  • 2020-11-20 (Fri.) 10:30 – 12:30
  • 資訊所新館106演講廳
摘要

Differential privacy has been widely applied to provide privacy guarantees by adding random noise to the function output. However, it inevitably fails in many high-stakes voting scenarios, where voting rules are required to be deterministic. In this work, we present the first framework for answering the question: ``How private are commonly-used voting rules?" Our answers are two-fold. First, we show that deterministic voting rules provide sufficient privacy in the sense of distributional differential privacy (DDP). We show that assuming the adversarial observer has uncertainty about individual votes, even publishing the histogram of votes achieves good DDP. Second, we introduce the notion of exact privacy to compare the privacy preserved in various commonly-studied voting rules, and obtain dichotomy theorems of exact DDP within a large subset of voting rules called generalized scoring rules.