Cryptology ePrint Archive: Report 2020/792

Trace-$\Sigma$: a privacy-preserving contact tracing app

Jean-François Biasse and Sriram Chelleppan and Sherzod Kariev and Noyem Khan and Lynette Menezes and Efe Seyitoglu and Charurut Somboonwit and Attila Yavuz

Abstract: We present a privacy-preserving protocol to anonymously collect information about a social graph. The typical application of our protocol is Bluetooth-enabled ``contact-tracing apps'' which record information about proximity between users to infer the risk of propagation of COVID-19 among them. The main contribution of this work is to enable a central server to construct an anonymous graph of interactions between users. This graph gives the central authority insight on the propagation of the virus, and allows it to run predictive models on it while protecting the privacy of users. The main technical tool we use is an accumulator scheme due to Camenisch and Lysyanskaya to keep track of the credentials of users, and prove accumulated credentials in Zero-Knowledge.

Category / Keywords: applications / Exposure notification, contact tracing, Zero-Knowledge proofs, sigma-protocols, Accumulators, Signatures of Knowledge, COVID-19.

Date: received 25 Jun 2020

Contact author: biasse at usf edu

Available format(s): PDF | BibTeX Citation

Version: 20200627:185311 (All versions of this report)

Short URL: ia.cr/2020/792


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