论文标题
与Corona-Warn-App模拟和可视化Covid-19接触跟踪，以增加对其隐私设计的理解
Simulating and visualizing COVID-19 contact tracing with Corona-Warn-App for increased understanding of its privacy-preserving design
论文作者
论文摘要
世界正处于一个持续的大流行期，即一个世纪前，世界上最后一次见到的规模。接触追踪是包含和破坏感染链的最关键和高效的工具之一，尤其是在感染性呼吸道疾病（如Covid-19）的情况下。由于我们时代的技术进步，我们现在拥有数字移动应用程序，例如Corona-Warn-App用于数字接触跟踪。但是，由于接触跟踪的侵入性性质，保留用户的隐私非常重要。隐私保护对于增加对该应用程序的信任并随后在隐私评估人群中提供广泛使用至关重要。在本文中，我们对Corona-Warn-App的工作进行了视觉模拟，以说明如何保留其用户的隐私，如何将其通知传染性联系人以及它如何帮助包含Covid-19的传播。
The world is under an ongoing pandemic, COVID-19, of a scale last seen a century ago. Contact tracing is one of the most critical and highly effective tools for containing and breaking the chain of infections especially in the case of infectious respiratory diseases like COVID-19. Thanks to the technological progress in our times, we now have digital mobile applications like the Corona-Warn-App for digital contact tracing. However, due to the invasive nature of contact tracing, it is very important to preserve the privacy of the users. Privacy preservation is important for increasing trust in the app and subsequently enabling its widespread usage in a privacy-valuing population. In this paper, we present a visual simulation of the working of the Corona-Warn-App to demonstrate how the privacy of its users is preserved, how they're notified of infectious contacts and how it helps in containing the spread of COVID-19.
