Threshold aggregation reporting systems promise a practical, privacy-preserving solution for developers to learn how their applications are used "\emph{in-the-wild}". Unfortunately, proposed systems to date prove impractical for wide scale adoption, suffering from a combination of requiring: \emph{i)} prohibitive trust assumptions; \emph{ii)} high computation costs; or \emph{iii)} massive user bases. As a result, adoption of truly-private approaches has been limited to only a small number of enormous (and enormously costly) projects. In this work, we improve the state of private data collection by proposing $\mathsf{STAR}$, a highly efficient, easily deployable system for providing cryptographically-enforced $\kappa$-anonymity protections on user data collection. The $\mathsf{STAR}$ protocol is easy to implement and cheap to run, all while providing privacy properties similar to, or exceeding the current state-of-the-art. Measurements of our open-source implementation of $\mathsf{STAR}$ find that it is $1773\times$ quicker, requires $62.4\times$ less communication, and is $24\times$ cheaper to run than the existing state-of-the-art.
翻译:阈值总和报告制度为开发者提供了一个实用的、隐私保护的解决方案。 不幸的是,迄今为止,拟议的系统证明不切实际,无法大规模采用,因为需要以下多种方法: emph{i)} 令人望而生畏的信任假设; 高计算成本; 或 emph{iii) 大型用户基础。因此,采用真正的私人办法仅限于少数大型(和昂贵的)项目。在这项工作中,我们通过提出美元(mathfsf{STAR})来改进私人数据收集状况。 美元(mathfsf{STAR})是高效的、易于部署的系统,用于提供加密强制的$(kappa) ; 令人难以信任的假设; 高计算成本; 或 或 emph{STAR} 大型用户基础。 因此,采用真正的私人办法仅限于少数大型(和高成本的)项目。 在这项工作中,我们通过提出美元(mathfsf{STAR}($) 美元(Star} $(一个高效的、可轻易部署的系统),在用户数据收集方面比目前更快地要求173美元更便宜的通信。