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Revisiting Multivariate Ring Learning with Errors and Its Applications on Lattice-Based Cryptography

Author

Listed:
  • Alberto Pedrouzo-Ulloa

    (AtlanTTic Research Center, Universidade de Vigo, 36310 Vigo, Spain)

  • Juan Ramón Troncoso-Pastoriza

    (Laboratory for Data Security, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland)

  • Nicolas Gama

    (Inpher, CH-1015 Lausanne, Switzerland)

  • Mariya Georgieva

    (Inpher, CH-1015 Lausanne, Switzerland)

  • Fernando Pérez-González

    (AtlanTTic Research Center, Universidade de Vigo, 36310 Vigo, Spain)

Abstract

The “Multivariate Ring Learning with Errors” problem was presented as a generalization of Ring Learning with Errors (RLWE), introducing efficiency improvements with respect to the RLWE counterpart thanks to its multivariate structure. Nevertheless, the recent attack presented by Bootland, Castryck and Vercauteren has some important consequences on the security of the multivariate RLWE problem with “non-coprime” cyclotomics; this attack transforms instances of m -RLWE with power-of-two cyclotomic polynomials of degree n = ∏ i n i into a set of RLWE samples with dimension max i { n i } . This is especially devastating for low-degree cyclotomics (e.g., Φ 4 ( x ) = 1 + x 2 ). In this work, we revisit the security of multivariate RLWE and propose new alternative instantiations of the problem that avoid the attack while still preserving the advantages of the multivariate structure, especially when using low-degree polynomials. Additionally, we show how to parameterize these instances in a secure and practical way, therefore enabling constructions and strategies based on m -RLWE that bring notable space and time efficiency improvements over current RLWE-based constructions.

Suggested Citation

  • Alberto Pedrouzo-Ulloa & Juan Ramón Troncoso-Pastoriza & Nicolas Gama & Mariya Georgieva & Fernando Pérez-González, 2021. "Revisiting Multivariate Ring Learning with Errors and Its Applications on Lattice-Based Cryptography," Mathematics, MDPI, vol. 9(8), pages 1-42, April.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:8:p:858-:d:535967
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