PAPR: Publicly Auditable Privacy Revocation for Anonymous Credentials
Paper in proceeding, 2023

We study the notion of anonymous credentials with Publicly Auditable Privacy Revocation (PAPR). PAPR credentials simultaneously provide conditional user privacy and auditable privacy revocation. The first property implies that users keep their identity private when authenticating unless and until an appointed authority requests to revoke this privacy, retroactively. The second property enforces that auditors can verify whether or not this authority has revoked privacy from an issued credential (i.e. learned the identity of the user who owns that credential), holding the authority accountable. In other words, the second property enriches conditionally anonymous credential systems with transparency by design, effectively discouraging such systems from being used for mass surveillance. In this work, we introduce the notion of a PAPR anonymous credential scheme, formalize it as an ideal functionality, and present constructions that are provably secure under standard assumptions in the Universal Composability framework. The core tool in our PAPR construction is a mechanism for randomly selecting an anonymous committee which users secret share their identity information towards, while hiding the identities of the committee members from the authority. As a consequence, in order to initiate the revocation process for a given credential, the authority is forced to post a request on a public bulletin board used as a broadcast channel to contact the anonymous committee that holds the keys needed to decrypt the identity connected to the credential. This mechanism makes the user de-anonymization publicly auditable.

Author

Joakim Brorsson

Lund University

Bernardo David

IT University of Copenhagen

Lorenzo Gentile

IT University of Copenhagen

Elena Pagnin

Chalmers, Computer Science and Engineering (Chalmers), Information Security

Paul Stankovski Wagner

Lund University

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 13871 LNCS 163-190
9783031308710 (ISBN)

Cryptographers’ Track at the RSA Conference, CT-RSA 2023
San Francisco, USA,

Subject Categories

Computer Science

DOI

10.1007/978-3-031-30872-7_7

More information

Latest update

6/29/2023