PACIFIC

Author:

Griffy Scott1ORCID,Lysyanskaya Anna1ORCID

Affiliation:

1. Brown University

Abstract

To be useful and widely accepted, automated contact tracing schemes (also called exposure notification) need to solve two seemingly contradictory problems at the same time: they need to protect the anonymity of honest users while also preventing malicious users from creating false alarms. In this paper, we provide, for the first time, an exposure notification construction that guarantees the same levels of privacy and integrity as existing schemes but with a fully malicious database (notably similar to Auerbach et al. CT-RSA 2021) without special restrictions on the adversary. We construct a new definition so that we can formally prove our construction secure. Our definition ensures the following integrity guarantees: no malicious user can cause exposure warnings in two locations at the same time and that any uploaded exposure notifications must be recent and not previously uploaded. Our construction is efficient, requiring only a single message to be broadcast at contact time no matter how many recipients are nearby. To notify contacts of potential infection, an infected user uploads data with size linear in the number of notifications, similar to other schemes. Linear upload complexity is not trivial with our assumptions and guarantees (a naive scheme would be quadratic). This linear complexity is achieved with a new primitive: zero knowledge subset proofs over commitments which is used by our "no cloning" proof protocol. We also introduce another new primitive: set commitments on equivalence classes, which makes each step of our construction more efficient. Both of these new primitives are of independent interest.

Publisher

International Association for Cryptologic Research

Reference44 articles.

1. Inverse-Sybil Attacks in Automated Contact Tracing;Benedikt Auerbach,2021

2. WHO Coronavirus (COVID-19) Dashboard;World Health Organization,2024

3. Contact Tracing Apps: Lessons Learned on Privacy, Autonomy, and the Need for Detailed and Thoughtful Implementation;Katie Hogan;JMIR Med Inform,2021

4. Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps;Cong Duc Tran;Technol Soc,2021

5. Decentralized Privacy-Preserving Proximity Tracing;Carmela Troncoso;CoRR,2020

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