ML-DSA is a post-quantum lattice-based digital signature algorithm (DSA) that the National Institute of Standards and Technology (NIST) recently standardized as FIPS 204. Remarkably, there are only a handful of published hardware designs and no open-source hardware implementations of complete ML-DSA. In this work, we present an efficient open-source hardware (OSH) design of ML-DSA, based on a Dilithium implementation by Beckwith et al. (FPT 2021). We also discuss the required modifications for migrating existing CRYSTALS-Dilithium implementations to match FIPS 204. Through optimized instruction scheduling in the ML-DSA rejection loop, which enables the pre-computation of critical variables, the average signing latency is improved by 16−36%.

In the recent search for additional post-quantum designs, multivariate quadratic equations (MQE) based designs have been receiving attention due to their small signature sizes. Unbalanced Oil and Vinegar (UOV) is an MQE-based digital signature (DS) scheme proposed over two decades ago. Although the mathematical security of UOV has been thoroughly analyzed, several practical side-channel attacks (SCA) have been shown on UOV based DS schemes. In this work, we perform a thorough analysis to identify the variables in UOV based DS schemes that can be exploited with passive SCA, specifically differential power attacks (DPA). Secondly, we introduce masking as a countermeasure to protect the sensitive components of UOV based schemes. We propose efficient masked gadgets for all the critical operations, including the masked dot-product and matrix-vector multiplication. We show that our gadgets are secure in the t-probing model through formal proofs, mechanically verified using the maskVerif tool. We implemented and demonstrated the practical feasibility of our arbitrary-order masking algorithms for UOV-Ip and UOV-III. We show that the masked signature generation of UOV-Ip performs up to 62% better than ML-DSA-44 and 99% better than Falcon-512. In addition, the security of our implementation is practically validated using the test vector leakage assessment (TVLA) methodology.

Recently, the construction of cryptographic schemes based on hard lattice problems has gained immense popularity. Apart from being quantum resistant, lattice-based cryptography allows a wide range of variations in the underlying hard problem. As cryptographic schemes can work in different environments under different operational constraints such as memory footprint, silicon area, efficiency, power requirement, and so on, such variations in the underlying hard problem are very useful for designers to construct different cryptographic schemes. In this work, we explore various design choices of lattice-based cryptography and their impact on performance in the real world. In particular, we propose a suite of key-encapsulation mechanisms based on the learning with rounding problem with a focus on improving different performance aspects of lattice-based cryptography. Our suite consists of three schemes. Our first scheme is Florete, which is designed for efficiency. The second scheme is Espada, which is aimed at improving parallelization, flexibility, and memory footprint. The last scheme is Sable, which can be considered an improved version in terms of key sizes and parameters of the Saber key-encapsulation mechanism, one of the finalists in the National Institute of Standards and Technology’s post-quantum standardization procedure. In this work, we have described our design rationale behind each scheme. Furthermore, to demonstrate the justification of our design decisions, we have provided software and hardware implementations. Our results show Florete is faster than most state-of-the-art KEMs on software platforms. For example, the key-generation algorithm of high-security version Florete outperforms the National Institute of Standards and Technology’s standard Kyber by 47%, the Federal Office for Information Security’s standard Frodo by 99%, and Saber by 57% on the ARM Cortex-M4 platform. Similarly, in hardware, Florete outperforms Frodo and NTRU Prime for all KEM operations. The scheme Espada requires less memory and area than the implementation of most state-of-the-art schemes. For example, the encapsulation algorithm of high-security version Espada uses 30% less stack memory than Kyber, 57% less stack memory than Frodo, and 67% less stack memory than Saber on the ARM Cortex-M4 platform. The implementations of Sable maintain a tradeoff between Florete and Espada regarding software performance and memory requirements. Sable outperforms Saber at least by 6% and Frodo by 99%. Through an efficient polynomial multiplier design, which exploits the small secret size, Sable outperforms most state-of-the-art KEMs, including Saber, Frodo, and NTRU Prime. The implementations of Sable that use number theoretic transform-based polynomial multiplication (SableNTT) surpass all the state-of-the-art schemes in performance, which are optimized for speed on the Cortext M4 platform. The performance benefit of SableNTT against Kyber lies in between 7-29%, 2-13% for Saber, and around 99% for Frodo.

Kyber was selected by NIST as a Post-Quantum Cryptography Key Encapsulation Mechanism standard. This means that the industry now needs to transition and adopt these new standards. One of the most demanding operations in Kyber is the modular arithmetic, making it a suitable target for optimization. This work offers a novel modular reduction design with the lowest area on Xilinx FPGA platforms. This novel design, through K-reduction and LUT-based reduction, utilizes 49 LUTs and 1 DSP as opposed to Xing and Li’s [XL21] 2021 CHES design requiring 90 LUTs and 1 DSP for one modular multiplication. Our design is the smallest modular multiplier reported as of today.