The Learning with Rounding (LWR) problem, introduced as a deterministic variant of Learning with Errors (LWE), has become a promising foundation for post-quantum cryptography. This Systematization of Knowledge (SoK) article presents a comprehensive survey of the theoretical foundations, algorithmic developments, and practical implementations of LWR-based cryptographic schemes. We introduce LWR within the broader landscape of lattice-based cryptography and post-quantum security, highlighting its advantages such as reduced randomness, improved efficiency, and enhanced side-channel resistance. We explore the evolution of security reductions from LWR to LWE, including recent advances that support practical parameter regimes and address challenges in both bounded and unbounded sample settings. This article systematically reviews existing LWR-based schemes — including Saber, Lizard, Florete, Espada, Sable, and SMAUG — analyzing their design choices, parameter sets, and performance tradeoffs. Furthermore, we examine the impact of LWR on side-channel resistance, failure probabilities, and masking efficiency, demonstrating its suitability for secure and efficient implementations. By consolidating the research spanning theory and practice, this SoK aims at guiding future cryptographic design and standardization efforts leveraging LWR.
The Learning with Rounding (LWR) problem, introduced as a deterministic variant of Learning with Errors (LWE), has become a promising foundation for post-quantum cryptography. This Systematization of Knowledge (SoK) article presents a comprehensive survey of the theoretical foundations, algorithmic developments, and practical implementations of LWR-based cryptographic schemes. We introduce LWR within the broader landscape of lattice-based cryptography and post-quantum security, highlighting its advantages such as reduced randomness, improved efficiency, and enhanced side-channel resistance. We explore the evolution of security reductions from LWR to LWE, including recent advances that support practical parameter regimes and address challenges in both bounded and unbounded sample settings. This article systematically reviews existing LWR-based schemes — including Saber, Lizard, Florete, Espada, Sable, and SMAUG — analyzing their design choices, parameter sets, and performance tradeoffs. Furthermore, we examine the impact of LWR on side-channel resistance, failure probabilities, and masking efficiency, demonstrating its suitability for secure and efficient implementations. By consolidating the research spanning theory and practice, this SoK aims at guiding future cryptographic design and standardization efforts leveraging LWR.
The ongoing transition to Post-Quantum Cryptography (PQC) has highlighted the need for cryptographic schemes that offer high security, strong performance, and fine-grained parameter selection. In lattice-based cryptography, particularly for the popular module variants of learning with errors (Module-LWE) and learning with rounding (Module-LWR) schemes based on power-of-two cyclotomics, existing constructions often force parameter choices that either overshoot or undershoot desired security levels due to structural constraints. In this work, we introduce a new class of techniques that are the advantages of both worlds: structured Module-LWE (or LWR) embeds more algebraic structure than a module such that it significantly improves performance, yet less structure than a power-of-two cyclotomic ring such that it still enables more flexible and efficient parameter selection. We present two concrete instances: a construction based on a radical extension of a two-power cyclotomic field denoted radical Ring-LWE (RR-LWE) or Ring-LWR (RR-LWR), and a cyclotomic block-ring module lattice approach (BRM-LWE or BRM-LWR). These new structured Module-LWE and LWR reduce the required number of uniformly random bytes in its matrix by a factor up to the module rank and allow efficient NTT implementations while enabling more granular security-performance trade-offs. We analyze the security of these constructions, provide practical parameter sets, and present implementation results demonstrating a performance improvement of up to 37% compared to an optimized implementation of ML-KEM. Our techniques apply to both key encapsulation mechanisms and digital signature schemes, offering a pathway to more adaptable and performant PQC standards.
Pseudorandom functions (PRFs) are a very important tool in cryptography, and the learning with rounding (LWR) problem is one of the main issues in their construction. LWR problem, is to find from ⌊ A s ⌋ p , where and is the rounding function. The LWR problem is considered a variant of the learning with error (LWE) problem, that is, to find s from b = A s + e , where , and LWE has been reduced to GapSVP and SIVP. The hardness of the lattice problems is the security foundation of the issued schemes. The best‐known reduction for LWR was completed using information‐theoretic entropy arguments, and the reduction requires q ≥ 2 n m p . It does not directly reduce to the closest vector problem (CVP) problem, but rather to the LWE problem. However, the reduction in the aforementioned work significantly reduces the difficulty of LWR. To more accurately characterize the hardness of LWR, this paper uses statistical approximation and a Quantum Fourier Transform to reduce LWR to the CVP, thereby ensuring the hardness of LWR. Furthermore, unlike the previous conclusions, our reduction involves minimal loss and has broad security conditions, requiring only that , where q and p are prime numbers and 0 < α < 1.
Abstract. The learning with rounding (LWR) problem, introduced by Banerjee, Peikert and Rosen [BPR12] at EUROCRYPT ’12, is a variant of learning with errors (LWE), where one replaces random errors with deterministic rounding. The LWR problem was shown to be as hard as LWE for a setting of parameters where the modulus and modulus-to-error ratio are super-polynomial. In this work we resolve the main open problem of [BPR12] and give a new reduction that works for a larger range of parameters, allowing for a polynomial modulus and modulus-to-error ratio. In particular, a smaller modulus gives us greater efficiency, and a smaller modulus-to-error ratio gives us greater security, which now follows from the worst-case hardness of GapSVP with polynomial (rather than super-polynomial) approximation factors. As a tool in the reduction, we show that there is a “lossy mode ” for the LWR problem, in which LWR samples only reveal partial information about the secret. This property gives us several interesting new applications, including a proof that LWR remains secure with weakly random secrets of sufficient minentropy, and very simple new constructions of deterministic encryption, lossy trapdoor functions and reusable extractors. Our approach is inspired by a technique of Goldwasser et al. [GKPV10] from ICS ’10, which implicitly showed the existence of a “lossy mode ” for LWE. By refining this technique, we also improve on the parameters of that work to only requiring a polynomial (instead of super-polynomial) modulus and modulus-to-error ratio.
The advancement of quantum computing threatens classical cryptographic systems, such as RSA and ECDSA, which can be broken by quantum algorithms like Shor's algorithm. This necessitates the development of post-quantum cryptographic systems resistant to quantum attacks. Lattice-based cryptography, particularly the Learning with Errors (LWE) and Learning with Rounding (LWR) problems, is a promising approach. This paper presents a threshold signature scheme based on the Kryzhovnik signature, an adaptation of the Crystals-Dilithium scheme for LWR. The scheme leverages the hardness of the Module Learning with Rounding (MLWR) and Module Short Integer Solution (MSIS) problems to ensure post-quantum security. It allows a group of N participants to collaboratively generate a signature, requiring at least t participants to create a valid signature, preventing forgery by individual participants. The scheme uses Shamir's Secret Sharing, ensuring the shared secret is never stored explicitly. Key advantages include efficiency, security, and threshold-based access control, making it suitable for IoT and other resource-constrained environments.
The Learning with Errors problem (LWE) and its variants are among the most popular assumptions underlying lattice-based cryptography. The Learning with Rounding problem (LWR) can be thought of as a deterministic variant of LWE. In this work, we present a thorough study of Somewhat Homomorphic Encryption schemes based on Ring-LWR that are the analogue of the Ring-LWE-based BFV scheme. Our main contribution is to present two new schemes, in the LPR and Regev paradigms, and give a thorough analysis of their security (provable and concrete). The technical tools we developed in the process may be of independent interest to the community. Our schemes inherit the many benefits of being based on LWR, including avoiding the need for expensive Gaussian sampling and improved ciphertext size. Indeed, we give a detailed comparison showing that our schemes marginally outperform the BFV scheme in terms of ciphertext size. Moreover, we show that both our schemes support RNS variants. Our Regev-type scheme can be seen as an improved generalisation of the only prior work in this direction (Costache-Smart, 2017). In particular, our scheme resolves the tangled modulus issue in the Costache-Smart proposal that led to unmanageable noise growth, and achieves a factor n improvement in the size of the public key.
The landscape of modern cryptography is fundamentally challenged by the advent of quantum computing. Current public-key cryptosystems, which form the bedrock of secure digital communication, rely on the computational hardness of problems such as integer factorization (RSA) and the discrete logarithm problem (ECC). However, Shor's algorithm, if implemented on a sufficiently powerful quantum computer, can efficiently break these schemes, rendering them insecure. This paper explores the critical transition from these classical number theory problems to lattice-based cryptography, presenting a comprehensive analysis of the motivations, theoretical underpinnings, and practical implications for forging post-quantum cryptographic security. We delve into the mathematical foundations of lattice problems, such as the Shortest Vector Problem (SVP) and Learning With Errors (LWE), which are believed to resist known quantum algorithms. Through a thorough literature review, we trace the evolution of cryptographic thought, detailing the vulnerabilities of pre-quantum schemes and the emergence of lattice-based constructions as leading candidates for post-quantum standardization. The methodology outlines a comparative theoretical analysis of security, efficiency, and robustness against both classical and quantum attacks. Results demonstrate the compelling advantages of lattice-based schemes in terms of provable security reductions and resistance to quantum threats, albeit with considerations for increased key and ciphertext sizes. The discussion highlights the challenges and opportunities in the deployment and standardization of these new cryptographic primitives, emphasizing their critical role in securing future digital infrastructures. This work concludes that lattice-based cryptography offers a robust and theoretically sound pathway to establishing enduring security in a quantum-threatened world.