Recent secure aggregation protocols enable privacy-preserving federated learning for high-dimensional models among thousands or even millions of participants. Due to the scale of these use cases, however, end-to-end empirical evaluation of these protocols is impossible. We present OLYMPIA, a framework for empirical evaluation of secure protocols via simulation. OLYMPIA provides an embedded domain-specific language for defining protocols, and a simulation framework for evaluating their performance. We implement several recent secure aggregation protocols using OLYMPIA, and perform the first empirical comparison of their end-to-end running times. We release OLYMPIA as open source.

翻译：近年来提出的安全聚合协议，使得在数千乃至数百万参与者之间实现高维模型的隐私保护联邦学习成为可能。然而，由于这些应用场景规模庞大，对这些协议进行端到端的实证评估是难以实现的。我们提出OLYMPIA——一个通过仿真对安全协议进行实证评估的框架。该框架包含用于定义协议的嵌入式领域特定语言，以及用于评估协议性能的仿真系统。我们利用OLYMPIA实现了多种近期提出的安全聚合协议，并首次对其端到端运行时间进行了实证比较。我们将OLYMPIA作为开源项目发布。