一句话：提出 COVIDGUARDIAN 自动评估接触追踪应用的安全与隐私弱点，并结合用户研究给出部署指南。
COVID-19 快速传播使人工接触者追踪变得困难，各地公共卫生部门开始采用移动应用进行自动接触追踪，但这些应用引发了安全与隐私担忧。本文提出自动化安全与隐私评估工具 COVIDGUARDIAN，结合个人身份信息（PII）的识别与分析、静态程序分析和数据流分析，以确定接触追踪应用中的安全与隐私弱点。在此基础上，作者开展用户研究以调查人们对接触追踪应用的担忧，并通过向厂商负责任披露相关问题，提出具体指南，揭示用户需求与应用表现之间的差距，旨在促进移动接触追踪的安全部署。
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.
@inproceedings{SunWXTCR21,
title = {An Empirical Assessment of Global COVID-19 Contact Tracing Applications},
author = {Ruoxi Sun and Wei Wang and Minhui Xue and Gareth Tyson and Seyit Camtepe and Damith C. Ranasinghe},
booktitle = {ICSE},
year = {2021},
doi = {10.1109/icse43902.2021.00101}
}