论文标题
全球COVID-19的经验评估接触示踪应用
An Empirical Assessment of Global COVID-19 Contact Tracing Applications
论文作者
论文摘要
Covid-19的迅速传播使手动接触的追踪变得困难。因此，各种公共卫生当局已经尝试使用移动应用程序（或“应用程序”）自动接触跟踪。但是，这些应用程序提出了安全和隐私问题。在本文中，我们提出了一种自动安全和隐私评估工具Covidguardian，该工具结合了个人识别信息（PII），静态程序分析和数据流分析的识别和分析，以确定安全性和隐私弱点。此外，鉴于我们的发现，我们进行了一项用户研究，以调查有关接触跟踪应用程序的担忧。我们希望Covidguardian以及通过负责披露供应商提出的问题可以为移动联系跟踪的安全部署做出贡献。为此，我们提供具体的指南，并突出显示用户需求和应用程序性能之间的差距。
The rapid spread of COVID-19 has made manual contact tracing difficult. Thus, various public health authorities have experimented with automatic contact tracing using mobile applications (or "apps"). These apps, however, have raised security and privacy concerns. In this paper, we propose an automated security and privacy assessment tool, COVIDGUARDIAN, which combines identification and analysis of Personal Identification Information (PII), static program analysis and data flow analysis, to determine security and privacy weaknesses. Furthermore, in light of our findings, we undertake a user study to investigate concerns regarding contact tracing apps. We hope that COVIDGUARDIAN, and the issues raised through responsible disclosure to vendors, can contribute to the safe deployment of mobile contact tracing. As part of this, we offer concrete guidelines, and highlight gaps between user requirements and app performance.
