OSKR/OKAI: Systematic Optimization of Key Encapsulation Mechanisms from Module Lattice
Shiyu Shen, Feng He, Zhichuang Liang, Yang Wang, Yunlei Zhao

TL;DR
This paper systematically optimizes lattice-based KEMs, especially Kyber and Aigis, through algorithmic improvements, novel NTT variants, and key size expansion techniques, resulting in faster, more compatible, and scalable cryptographic implementations.
Contribution
It introduces a systematic optimization framework for MLWE-based KEMs, including a new hybrid NTT variant and compatibility-focused enhancements for Kyber and Aigis.
Findings
AKCN-based decryption is faster and less error-prone.
The hybrid-NTT (H-NTT) offers optimal computational complexity.
The proposed methods improve key expansion and implementation compatibility.
Abstract
In this work, we make \emph{systematic} optimizations of key encapsulation mechanisms (KEM) based on module learning-with-errors (MLWE), covering algorithmic design, fundamental operation of number-theoretic transform (NTT), approaches to expanding encapsulated key size, and optimized implementation coding. We focus on Kyber (now in the Round-3 finalist of NIST PQC standardization) and Aigis (a variant of Kyber proposed at PKC 2020). By careful analysis, we first observe that the algorithmic design of Kyber and Aigis can be optimized by the mechanism of asymmetric key consensus with noise (AKCN) proposed in \cite{JZ16,JZ19}. Specifically, the decryption process can be simplified with AKCN, leading to a both faster and less error-prone decryption process. Moreover, the AKCN-based optimized version has perfect compatibility with the deployment of Kyber/Aigis in reality, as they can run…
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Taxonomy
TopicsCryptography and Data Security · Coding theory and cryptography · Cryptographic Implementations and Security
