Updatable Privacy-Preserving Blueprints
Paper i proceeding, 2025

Privacy-preserving blueprint schemes (Kohlweiss et al., EUROCRYPT’23) offer a mechanism for safeguarding user’s privacy while allowing for specific legitimate controls by a designated auditor agent. These schemes enable users to create escrows encrypting the result of evaluating a function y=P(t,x), with P being publicly known, t a secret used during the auditor’s key generation, and x the user’s private input. Crucially, escrows only disclose the blueprinting result y=P(t,x) to the designated auditor, even in cases where the auditor is fully compromised. The original definition and construction only support the evaluation of functions P on an input x provided by a single user. We address this limitation by introducing updatable privacy-preserving blueprint schemes (UPPB), which enhance the original notion with the ability for multiple users to non-interactively update the private user input x while blueprinting. Moreover, UPPBs contain a proof that y is the result of a sequence of valid updates, while revealing nothing else about the private inputs {xi} of updates. As in the case of privacy-preserving blueprints, we first observe that UPPBs can be realized via a generic construction for arbitrary predicates P based on FHE and NIZKs. Our main result is uBlu, an efficient instantiation for a specific predicate comparing the values x and t, where x is the cumulative sum of users’ private inputs and t is a fixed private value provided by the auditor in the setup phase. This rather specific setting already finds interesting applications such as privacy-preserving anti-money laundering and location tracking, and can be extended to support more generic predicates. From the technical perspective, we devise a novel technique to keep the escrow size concise, independent of the number of updates, and reasonable for practical applications. We achieve this via a novel characterization of malleability for the algebraic NIZK by Couteau and Hartmann (CRYPTO’20) that allows for an additive update function.

Privacy-Preserving Blueprints

Updatable NIZKs

Författare

Bernardo David

IT-Universitetet i Kobenhavn

Felix Engelmann

Lunds universitet

Tore Frederiksen

Zama

Markulf Kohlweiss

University of Edinburgh

Elena Pagnin

Chalmers, Data- och informationsteknik, Informationssäkerhet

Mikhail Volkhov

University of Edinburgh

O1Labs

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

03029743 (ISSN) 16113349 (eISSN)

Vol. 15484 LNCS 105-139
9789819608744 (ISBN)

30th Annual International Conference on the Theory and Application of Cryptology and Information Security, ASIACRYPT 2024
Kolkata, India,

Ämneskategorier

Datavetenskap (datalogi)

DOI

10.1007/978-981-96-0875-1_4

Mer information

Senast uppdaterat

2025-01-10