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Adaptively Secure Identity-Based Encryption from Middle-Product Learning with Errors

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Information Security and Privacy (ACISP 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13915))

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Abstract

Introduced in 2017, Middle-Product Learning with Errors (MPLWE) and its variants offer a way to construct cryptographic primitives which preserve the efficiency of those based on Polynomial-LWE (PLWE) while being at least as secure as them over a broad choice of number fields. Based on MPLWE, a series of cryptographic schemes have been proposed, including public key encryption (PKE), digital signature, and identity-based encryption (IBE). In this paper, we extend this line of research and propose a new IBE scheme that is adaptively secure in the standard model from MPLWE. Existing IBE schemes from MPLWE only offer selective security or rely on the random oracle model. We follow the blueprint of Agrawal et al. at EUROCRYPT2010 and adapt the well-known partitioning technique to the MPLWE setting. The resulting scheme offers similar efficiency to schemes based on PLWE under a milder assumption.

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Authors and Affiliations

  1. University of Hong Kong, Pok Fu Lam, China

    Jingjing Fan

  2. The Hong Kong Polytechnic University, Hung Hom, China

    Xingye Lu & Man Ho Au

Authors
  1. Jingjing Fan
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  2. Xingye Lu
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  3. Man Ho Au
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Correspondence to Xingye Lu .

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Editors and Affiliations

  1. Queensland University of Technology, Brisbane, QLD, Australia

    Leonie Simpson

  2. Queensland University of Technology, Brisbane, QLD, Australia

    Mir Ali Rezazadeh Baee

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Fan, J., Lu, X., Au, M.H. (2023). Adaptively Secure Identity-Based Encryption from Middle-Product Learning with Errors. In: Simpson, L., Rezazadeh Baee, M.A. (eds) Information Security and Privacy. ACISP 2023. Lecture Notes in Computer Science, vol 13915. Springer, Cham. https://doi.org/10.1007/978-3-031-35486-1_15

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  • DOI: https://doi.org/10.1007/978-3-031-35486-1_15

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  • Online ISBN: 978-3-031-35486-1

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