How Private Are Commonly-Used Voting Rules?

Understand

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).