PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols
Fabrizio Cicala, Weicheng Wang, Tianhao Wang, Ninghui Li, Elisa, Bertino, Faming Liang, Yang Yang

TL;DR
This paper introduces PURE, a comprehensive framework for analyzing proximity-based contact tracing protocols focusing on privacy, utility, resiliency, and efficiency, by examining their design choices and properties.
Contribution
It systematically identifies key properties and design choices of PCT protocols, enabling thorough analysis and comparison of existing solutions.
Findings
PURE framework covers privacy, utility, resiliency, efficiency
Design choices significantly impact protocol properties
Provides a basis for evaluating and improving contact tracing protocols
Abstract
Many proximity-based tracing (PCT) protocols have been proposed and deployed to combat the spreading of COVID-19. In this paper, we take a systematic approach to analyze PCT protocols. We identify a list of desired properties of a contact tracing design from the four aspects of Privacy, Utility, Resiliency, and Efficiency (PURE). We also identify two main design choices for PCT protocols: what information patients report to the server, and which party performs the matching. These two choices determine most of the PURE properties and enable us to conduct a comprehensive analysis and comparison of the existing protocols.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCOVID-19 Digital Contact Tracing · Privacy-Preserving Technologies in Data · Privacy, Security, and Data Protection
