论文标题
TraceSecure：迈向隐私保护联系人跟踪
TraceSecure: Towards Privacy Preserving Contact Tracing
论文作者
论文摘要
接触示踪已被广泛用于打击COVID-19的扩散。已经开发了许多应用程序，这些应用程序可以自动根据用户生成的位置和交互数据自动进行跟踪。但是，在使用这些应用程序时，对用户数据的隐私和安全性存在疑问。这些关注点对于感染病毒的用户至关重要，因为通常需要释放所有数据。由于需要保护用户隐私的需要，我们就此问题提出了两个解决方案。我们的第一个解决方案基于当前的“基于消息”的方法，第二个解决方案从秘密共享和加性同构加密中利用了想法。
Contact tracing is being widely employed to combat the spread of COVID-19. Many apps have been developed that allow for tracing to be done automatically based off location and interaction data generated by users. There are concerns, however, regarding the privacy and security of users data when using these apps. These concerns are paramount for users who contract the virus, as they are generally required to release all their data. Motivated by the need to protect users privacy we propose two solutions to this problem. Our first solution builds on current "message based" methods and our second leverages ideas from secret sharing and additively homomorphic encryption.
