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Shorter Messages and Faster Post-Quantum Encryption with Round5 on Cortex M

机译:在Cortex M上使用Round5缩短消息长度并提高后量子加密速度

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Round5 is a Public Key Encryption and Key Encapsulation Mechanism (KEM) based on General Learning with Rounding (GLWR), a lattice problem. We argue that the ring variant of GLWR is better suited for embedded targets than the more common RLWE (Ring Learning With Errors) due to significantly shorter keys and messages. Round5 incorporates GLWR with error correction, building on design features from NIST Post-Quantum Standardization candidates Round2 and Hila5. The proposal avoids Number Theoretic Transforms (NTT), allowing more flexibility in parameter selection and making it simpler to implement. We discuss implementation techniques of Rounds ring variants and compare them to other NIST PQC candidates on lightweight Cortex M4 platform. We show that the current development version of Round5 offers not only the shortest key and ciphertext sizes among Lattice-based candidates, but also has leading performance and implementation size characteristics.
机译:Round5是基于通用学习与舍入(GLWR)(一种晶格问题)的公钥加密和密钥封装机制(KEM)。我们认为,GLWR的环形变体比更常见的RLWE(有错误的环形学习)更适合嵌入式目标,因为它的密钥和消息短得多。 Round5在基于NIST量子后标准化候选者Round2和Hila5的设计功能的基础上,将GLWR与纠错功能结合在一起。该建议避免了数论转换(NTT),从而在参数选择方面提供了更大的灵活性,并使其更易于实现。我们讨论了Rounds圆环变体的实现技术,并将它们与轻量级Cortex M4平台上的其他NIST PQC候选对象进行比较。我们显示,Round5的当前开发版本不仅提供了基于莱迪思的候选者中最短的密钥和密文大小,而且还具有领先的性能和实现大小特征。

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