论文标题
通过洗牌签名进行隐私放大
Privacy Amplification via Shuffled Check-Ins
论文作者
论文摘要
我们研究了一种称为改组的分布式计算的协议，该协议可实现强大的隐私保证，而无需超越可信赖的改组者的任何进一步的信任假设。与大多数现有的工作不同，洗牌仪允许客户做出独立和随机决策以参与计算，从而消除了对服务器发射的亚采样的需求。利用差异隐私，我们表明，通过基于R {é} NYI差异差异隐私的新颖分析，通过隐私放大来确保签出的紧密隐私，从而改善了对现有工作的隐私会计。我们还引入了一种数字方法，以跟踪包括高斯机制在内的通用洗牌机制的隐私，这是对文献中本地/洗牌模型中分布式设置下的通用机制的首次评估。还提供了经验研究以证明所提出方法的功效。
We study a protocol for distributed computation called shuffled check-in, which achieves strong privacy guarantees without requiring any further trust assumptions beyond a trusted shuffler. Unlike most existing work, shuffled check-in allows clients to make independent and random decisions to participate in the computation, removing the need for server-initiated subsampling. Leveraging differential privacy, we show that shuffled check-in achieves tight privacy guarantees through privacy amplification, with a novel analysis based on R{é}nyi differential privacy that improves privacy accounting over existing work. We also introduce a numerical approach to track the privacy of generic shuffling mechanisms, including Gaussian mechanism, which is the first evaluation of a generic mechanism under the distributed setting within the local/shuffle model in the literature. Empirical studies are also given to demonstrate the efficacy of the proposed approach.
