Safer Illinois and RokWall: Privacy Preserving University Health Apps\n for COVID-19

COVID-19 has fundamentally disrupted the way we live. Government bodies,\nuniversities, and companies worldwide are rapidly developing technologies to\ncombat the COVID-19 pandemic and safely reopen society. Essential analytics\ntools such as contact tracing, super-spreader event detection, and exposure\nmapping require collecting and analyzing sensitive user information. The\nincreasing use of such powerful data-driven applications necessitates a secure,\nprivacy-preserving infrastructure for computation on personal data. In this\npaper, we analyze two such computing infrastructures under development at the\nUniversity of Illinois at Urbana-Champaign to track and mitigate the spread of\nCOVID-19. First, we present Safer Illinois, a system for decentralized health\nanalytics supporting two applications currently deployed with widespread\nadoption: digital contact tracing and COVID-19 status cards. Second, we\nintroduce the RokWall architecture for privacy-preserving centralized data\nanalytics on sensitive user data. We discuss the architecture of these systems,\ndesign choices, threat models considered, and the challenges we experienced in\ndeveloping production-ready systems for sensitive data analysis.\n