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Privacy-Preserving Blueprints

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Advances in Cryptology – EUROCRYPT 2023 (EUROCRYPT 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14005))

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Abstract

If everyone were to use anonymous credentials for all access control needs, it would be impossible to trace wrongdoers, by design. This would make legitimate controls, such as tracing illicit trade and terror suspects, impossible to carry out. Here, we propose a privacy-preserving blueprint capability that allows an auditor to publish an encoding \(\textsf{pk}_{\textsf{A}}\) of the function \(f(x,\cdot )\) for a publicly known function f and a secret input x. For example, x may be a secret watchlist, and f(x, y) may return y if \(y\in x\). On input her data y and the auditor’s \(\textsf{pk}_{\textsf{A}}\), a user can compute an escrow \(Z\) such that anyone can verify that \(Z\) was computed correctly from the user’s credential attributes, and moreover, the auditor can recover f(x, y) from \(Z\). Our contributions are:

  • We define secure f-blueprint systems; our definition is designed to provide a modular extension to anonymous credential systems.

  • We show that secure f-blueprint systems can be constructed for all functions f from fully homomorphic encryption and NIZK proof systems. This result is of theoretical interest but is not efficient enough for practical use.

  • We realize an optimal blueprint system under the DDH assumption in the random-oracle model for the watchlist function.

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Notes

  1. 1.

    E.g., \({\textsf{A}}\) can prove that \(x\) does not contain journalists, but does contain all Russian oligarchs on the OFAC’s sanctions list. https://home.treasury.gov/policy-issues/financial-sanctions.

  2. 2.

    For example, if \(x\) is a list \((x_1,\ldots ,x_n)\) and \(f(x,y)\) checks if \(y= x_i\) for some i, \(g(y)\) can be a one-way permutation: in order to determine whether \(y\) is on the list, it is sufficient to compute \(g(x_j)\) and compare it to \(y^*=g(y)\).

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Acknowledgment

We thank Scott Griffy and Peihan Miao for helpful discussions, and the anonymous referees for constructive feedback. This research was supported by NSF awards #2154170 and #2154941, and by grants from Meta.

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  1. University of Edinburgh and Input Output, Edinburgh, UK

    Markulf Kohlweiss

  2. Brown University, Providence, USA

    Anna Lysyanskaya & An Nguyen

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    Carmit Hazay

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    Martijn Stam

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Kohlweiss, M., Lysyanskaya, A., Nguyen, A. (2023). Privacy-Preserving Blueprints. In: Hazay, C., Stam, M. (eds) Advances in Cryptology – EUROCRYPT 2023. EUROCRYPT 2023. Lecture Notes in Computer Science, vol 14005. Springer, Cham. https://doi.org/10.1007/978-3-031-30617-4_20

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