Assessing Disease Exposure Risk with Location Data: A Proposal for Cryptographic Preservation of Privacy

Abstract

Governments and researchers around the world are implementing digital contact tracing solutions to stem the spread of infectious disease, namely COVID-19. Many of these solutions threaten individual rights and privacy. Our goal is to break past the false dichotomy of effective versus privacy-preserving contact tracing. We offer an alternative approach to assess and communicate users' risk of exposure to an infectious disease while preserving individual privacy. Our proposal uses recent GPS location histories, which are transformed and encrypted, and a private set intersection protocol to interface with a semi-trusted authority. There have been other recent proposals for privacy-preserving contact tracing, based on Bluetooth and decentralization, that could further eliminate the need for trust in authority. However, solutions with Bluetooth are currently limited to certain devices and contexts while decentralization adds complexity. The goal of this work is two-fold: we aim to propose a location-based system that is more privacy-preserving than what is currently being adopted by governments around the world, and that is also practical to implement with the immediacy needed to stem a viral outbreak.

References in corpus (3)

• Contact Tracing Mobile Apps for COVID-19: Privacy Considerations and Related Trade-offs
• Apps Gone Rogue: Maintaining Personal Privacy in an Epidemic
• Countering Gattaca: Efficient and Secure Testing of Fully-Sequenced Human Genomes (Full Version)

Cited by in corpus (17)

• WiFiTrace: Network-based Contact Tracing for Infectious Diseases Using Passive WiFi Sensing
• Privacy Guidelines for Contact Tracing Applications
• Review and Critical Analysis of Privacy-preserving Infection Tracking and Contact Tracing
• Challenges of Equitable Vaccine Distribution in the COVID-19 Pandemic
• Online Information Search During COVID-19
• Bluetooth Smartphone Apps: Are they the most private and effective solution for COVID-19 contact tracing?
• A Privacy-preserving Mobile and Fog Computing Framework to Trace and Prevent COVID-19 Community Transmission
• SpreadMeNot: A Provably Secure and Privacy-Preserving Contact Tracing Protocol
• A note on blind contact tracing at scale with applications to the COVID-19 pandemic
• PPContactTracing: A Privacy-Preserving Contact Tracing Protocol for COVID-19 Pandemic
• vContact: Private WiFi-based Contact Tracing with Virus Lifespan
• An Empirical Evaluation of Bluetooth-based Decentralized Contact Tracing in Crowds
• PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols
• KHOVID: Interoperable Privacy Preserving Digital Contact Tracing
• A Note on Cryptographic Algorithms for Private Data Analysis in Contact Tracing Applications
• Secure Data Hiding for Contact Tracing
• SNARKs to the rescue: proof-of-contact in zero knowledge