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Annual International Conference on the Theory and Applications of Cryptographic Techniques

EUROCRYPT 2021: Advances in Cryptology – EUROCRYPT 2021 pp 528–558Cite as

On Bounded Distance Decoding with Predicate: Breaking the “Lattice Barrier” for the Hidden Number Problem

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12696))

Abstract

Lattice-based algorithms in cryptanalysis often search for a target vector satisfying integer linear constraints as a shortest or closest vector in some lattice. In this work, we observe that these formulations may discard non-linear information from the underlying application that can be used to distinguish the target vector even when it is far from being uniquely close or short.

We formalize lattice problems augmented with a predicate distinguishing a target vector and give algorithms for solving instances of these problems. We apply our techniques to lattice-based approaches for solving the Hidden Number Problem, a popular technique for recovering secret DSA or ECDSA keys in side-channel attacks, and demonstrate that our algorithms succeed in recovering the signing key for instances that were previously believed to be unsolvable using lattice approaches. We carried out extensive experiments using our estimation and solving framework, which we also make available with this work.

N. Heninger—The research of MA was supported by EPSRC grants EP/S020330/1, EP/S02087X/1, by the European Union Horizon 2020 Research and Innovation Program Grant 780701 and Innovate UK grant AQuaSec; NH was supported by the US NSF under grants no. 1513671, 1651344, and 1913210. Part of this work was done while the authors were visiting the Simons Institute for the Theory of Computing. Our experiments were carried out on Cisco UCS equipment donated by Cisco and housed at UCSD. The full version of this work is available at https://ia.cr/2020/1540.

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Notes

  1. 1.

    We note that this technique conflicts with “dimensions for free” [5, 32] and thus the expected performance improvement when arbitrarily many samples are available is smaller compared to state-of-the-art sieving (see Sect. 5.3 for details).

  2. 2.

    For the purposes of this work, the CVP technique used in [17] is not entirely clear from the account given there. We confirmed with the authors that is the analogous strategy to their SVP approach: CVP enumeration interleaved with tours of BKZ.

  3. 3.

    In G6K the 3-Sieve is configured to use a database of size \(2^{0.205\,d+o(d)}\) by default, which lowers its time complexity.

  4. 4.

    The constant is typically defined as \(\Vert \boldsymbol{b}_{0}\Vert \approx \delta _{\beta }^{d} \cdot {\mathrm {Vol}(\varLambda )}^{1/d}\) in the literature. From the perspective of the (worst-case) analysis of underlying algorithms, though, normalizing by \(d-1\) rather than \(d\) is appropriate.

  5. 5.

    The radius \(\sqrt{4/3} \cdot \mathrm {gh}(\varLambda )\) can be parameterized in sieving algorithms by adapting the required angle for a reduction and thus increasing the database size. This was used in e.g. [31] to find approximate Voronoi cells.

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Acknowledgments

We thank Joe Rowell and Jianwei Li for helpful discussions on an earlier draft of this work, Daniel Genkin for suggesting additional references and a discussion on error resilience, Noam Nissan for feedback on our implementation, and Samuel Neves for helpful suggestions on our characterization of previous work.

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  1. Information Security Group, Royal Holloway, University of London, London, UK

    Martin R. Albrecht

  2. University of California, San Diego, USA

    Nadia Heninger

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Albrecht, M.R., Heninger, N. (2021). On Bounded Distance Decoding with Predicate: Breaking the “Lattice Barrier” for the Hidden Number Problem. In: Canteaut, A., Standaert, FX. (eds) Advances in Cryptology – EUROCRYPT 2021. EUROCRYPT 2021. Lecture Notes in Computer Science(), vol 12696. Springer, Cham. https://doi.org/10.1007/978-3-030-77870-5_19

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