论文标题
LinkedIn的受众互动API：按大规模保存数据分析系统的隐私
LinkedIn's Audience Engagements API: A Privacy Preserving Data Analytics System at Scale
论文作者
论文摘要
我们提出了一个利用差异隐私来保护LinkedIn成员数据的隐私系统，同时还提供了受众参与见解，以使营销分析与应用程序相关。我们详细介绍了用于提供可用于现有的实时数据分析平台的差异私有算法和其他隐私保护措施，特别是与开源Pinot系统一起使用的结果。我们的隐私系统提供用户级的隐私保证。作为我们隐私系统的一部分，我们包括一项预算管理服务，该服务对分析师的返回结果强制执行严格的差异隐私预算。该预算管理服务将鉴别隐私的最新研究汇集到产品中，以维护固定的差异隐私预算。
We present a privacy system that leverages differential privacy to protect LinkedIn members' data while also providing audience engagement insights to enable marketing analytics related applications. We detail the differentially private algorithms and other privacy safeguards used to provide results that can be used with existing real-time data analytics platforms, specifically with the open sourced Pinot system. Our privacy system provides user-level privacy guarantees. As part of our privacy system, we include a budget management service that enforces a strict differential privacy budget on the returned results to the analyst. This budget management service brings together the latest research in differential privacy into a product to maintain utility given a fixed differential privacy budget.
