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Single-Server Private Information Retrieval with Sublinear Amortized Time

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Advances in Cryptology – EUROCRYPT 2022 (EUROCRYPT 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13276))

Abstract

We construct new private-information-retrieval protocols in the single-server setting. Our schemes allow a client to privately fetch a sequence of database records from a server, while the server answers each query in average time sublinear in the database size. Specifically, we introduce the first single-server private-information-retrieval schemes that have sublinear amortized server time, require sublinear additional storage, and allow the client to make her queries adaptively. Our protocols rely only on standard cryptographic assumptions (decision Diffie-Hellman, quadratic residuosity, learning with errors, etc.). They work by having the client first fetch a small “hint” about the database contents from the server. Generating this hint requires server time linear in the database size. Thereafter, the client can use the hint to make a bounded number of adaptive queries to the server, which the server answers in sublinear time—yielding sublinear amortized cost. Finally, we give lower bounds proving that our most efficient scheme is optimal with respect to the trade-off it achieves between server online time and client storage.

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Acknowledgements

We thank David Wu and Yuval Ishai for reading an early draft of this work and for their helpful suggestions on how to improve it. We thank Yevgeniy Dodis, Siyao Guo, and Sandro Coretti for answering questions about presampling. We deeply appreciate the support and technical advice that Dan Boneh gave on this project from the very start. Part of this work was done when the third author was a student at Stanford University. This work was supported in part by the National Science Foundation (Award CNS-2054869), a gift from Google, a Facebook Research Award, and the Fintech@CSAIL Initiative, as well as the National Science Foundation Graduate Research Fellowship under Grant No. 1745302 and an EECS Great Educators Fellowship.

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Authors and Affiliations

  1. MIT, Cambridge, MA, USA

    Henry Corrigan-Gibbs & Alexandra Henzinger

  2. Fordefi, Tel Aviv, Israel

    Dmitry Kogan

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  1. Henry Corrigan-Gibbs
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  2. Alexandra Henzinger
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Correspondence to Alexandra Henzinger .

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  1. University of Haifa, Haifa, Haifa, Israel

    Orr Dunkelman

  2. University of Warsaw, Warsaw, Poland

    Stefan Dziembowski

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Corrigan-Gibbs, H., Henzinger, A., Kogan, D. (2022). Single-Server Private Information Retrieval with Sublinear Amortized Time. In: Dunkelman, O., Dziembowski, S. (eds) Advances in Cryptology – EUROCRYPT 2022. EUROCRYPT 2022. Lecture Notes in Computer Science, vol 13276. Springer, Cham. https://doi.org/10.1007/978-3-031-07085-3_1

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  • DOI: https://doi.org/10.1007/978-3-031-07085-3_1

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