论文标题
信念功能的当地差异隐私
Local Differential Privacy for Belief Functions
论文作者
论文摘要
在本文中，我们提出了有关信仰功能的当地差异隐私的两个新定义。一个基于Shafer的随机编码消息的语义，另一个是从不精确概率的角度来看。我们表明，诸如组成和后处理之类的基本属性也适用于我们的新定义。此外，我们为这些定义提供了一个假设测试框架，并研究了离散分布估算中隐私和效用之间的“不知道”的影响。
In this paper, we propose two new definitions of local differential privacy for belief functions. One is based on Shafer's semantics of randomly coded messages and the other from the perspective of imprecise probabilities. We show that such basic properties as composition and post-processing also hold for our new definitions. Moreover, we provide a hypothesis testing framework for these definitions and study the effect of "don't know" in the trade-off between privacy and utility in discrete distribution estimation.
