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Smooth Hash Proof System Based on the Learning With Errors Problem With Multi-Bit Key Output

Authors: Momeng Liu; Yupu Hu; Shanshan Zhang; Linming Gong;

Smooth Hash Proof System Based on the Learning With Errors Problem With Multi-Bit Key Output

Abstract

Since hash proof system (HPS) can be utilized to build versatilely cryptographic schemes, the study on realizing this cryptographic primitive has been a very active research area. With the increasing concerns on the huge progress in quantum computing, it urges cryptographers to explore the existence of quantum-resistant HPS schemes, such as the one relying on some lattice-based assumptions. However, most lattice-based HPS proposals are relatively inefficient (e.g., simply outputting one-bit key), even though lattice-based schemes can enjoy many advantageous features: worst-case to average-case reduction, resistance so far to quantum algorithms, and good asymptotic efficiency. Therefore, efficient HPS schemes based on lattice problems are deeply in demand. Through a comprehensive analysis, we found that some lattice-based HPS schemes can be rephrased as their corresponding key encapsulation mechanism (KEM) forms, which generally rely on diverse reconciliation mechanisms and directly imply key exchange protocols under lattice-based assumptions. In this paper, inspired by a novel reconciliation mechanism based on the learning with errors (LWE) problem, we first properly adapt this LWE-based reconciliation mechanism for arbitrary modulus. Then using this improved reconciliation mechanism, we propose an efficient LWE-based HPS scheme which can generate multiple encapsulated key bits and perform better in both computation and storage costs than other related results. Moreover, our proposed lattice-based HPS scheme can be also extended to identity-based and updatable settings for demonstrating its diverse applications.

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Keywords

Hash proof system, key encapsulation mechanism, key exchange, lattice-based cryptography, Electrical engineering. Electronics. Nuclear engineering, learning with errors, TK1-9971

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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