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

Jingjing Fan; Xingye Lu; Man Ho Au

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

Jingjing Fan, Xingye Lu, Man Ho Au

Department of Computing

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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.

Original language	English
Title of host publication	Information Security and Privacy 28th Australasian Conference, ACISP 2023, Brisbane, QLD, Australia, July 5–7, 2023, Proceedings
Publisher	Springer Cham
Pages	320–340
Volume	13915
Publication status	Published - 15 Jun 2024

Cite this

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title = "Adaptively Secure Identity-Based Encryption from Middle-Product Learning with Errors",

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.",

author = "Jingjing Fan and Xingye Lu and Au, {Man Ho}",

year = "2024",

month = jun,

day = "15",

language = "English",

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pages = "320–340",

booktitle = "Information Security and Privacy 28th Australasian Conference, ACISP 2023, Brisbane, QLD, Australia, July 5–7, 2023, Proceedings",

publisher = "Springer Cham",

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Adaptively Secure Identity-Based Encryption from Middle-Product Learning with Errors. / Fan, Jingjing; Lu, Xingye; Au, Man Ho.
Information Security and Privacy 28th Australasian Conference, ACISP 2023, Brisbane, QLD, Australia, July 5–7, 2023, Proceedings. Vol. 13915 Springer Cham, 2024. p. 320–340.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Adaptively Secure Identity-Based Encryption from Middle-Product Learning with Errors

AU - Fan, Jingjing

AU - Lu, Xingye

AU - Au, Man Ho

PY - 2024/6/15

Y1 - 2024/6/15

N2 - 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.

AB - 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.

UR - http://dx.doi.org/10.1007/978-3-031-35486-1_15

M3 - Conference article published in proceeding or book

VL - 13915

SP - 320

EP - 340

BT - Information Security and Privacy 28th Australasian Conference, ACISP 2023, Brisbane, QLD, Australia, July 5–7, 2023, Proceedings

PB - Springer Cham

ER -

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

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