Discrete Gaussian Sampling on lattices is a fundamental problem in lattice-based cryptography. It appears both in basic cryptographic primitives such as digital signatures and as an important cryptanalysis building block for solving hard lattice problems. In this paper, we show a quantum algorithm based on the quantum rejection sampling technique whose complexity is asymptotically quadratically faster than its classical counterpart in [Wang & Ling, IEEE Trans. Inf. Theory 2019]. Our sampler outputs a quantum state which can either be measured to get the desired distribution or be used directly as such in other quantum algorithms. By doing so, we derive two versions of quantum dual attacks that improve upon the previous ones in [Pouly & Shen, EUROCRYPT 2024]. The two versions are incomparable, each having distinct advantages (speed vs memory requirement). The second version is particularly interesting as it requires only polynomial classical and quantum memory, excluding the classical memory used in the preprocessing step of the Discrete Gaussian sampler. Our quantum Discrete Gaussian sampler can also be used to speed up the algorithm for solving the Short Integer Solution problem, in any norm, of [Bollauf, Pouly & Shen, ePrint 2026/225].
Discrete Gaussian Sampling on lattices is a fundamental problem in lattice-based cryptography. It appears both in basic cryptographic primitives such as digital signatures and as an important cryptanalysis building block for solving hard lattice problems. In this paper, we show a quantum algorithm based on the quantum rejection sampling technique whose complexity is asymptotically quadratically faster than its classical counterpart in [Wang & Ling, IEEE Trans. Inf. Theory 2019]. Our sampler outputs a quantum state which can either be measured to get the desired distribution or be used directly as such in other quantum algorithms. By doing so, we derive two versions of quantum dual attacks that improve upon the previous ones in [Pouly & Shen, EUROCRYPT 2024]. The two versions are incomparable, each having distinct advantages (speed vs memory requirement). The second version is particularly interesting as it requires only polynomial classical and quantum memory, excluding the classical memory used in the preprocessing step of the Discrete Gaussian sampler. Our quantum Discrete Gaussian sampler can also be used to speed up the algorithm for solving the Short Integer Solution problem, in any norm, of [Bollauf, Pouly & Shen, ePrint 2026/225].
In this work, we revisit the dual attack and GPV trapdoor sampling, focusing on the lattice Gaussian sampling term, which can be a significant bottleneck in the overall complexity. We show that this sampling step can be quantumly accelerated by combining the lower bound underlying Wang and Ling's analysis of Klein's algorithm with the quantum rejection sampling (QRS) framework proposed by Ozols et al. Specifically, this lower bound gives precisely the pointwise domination condition required for quantum rejection sampling when given coherent oracle access to a truncated Klein proposal distribution, which yields a quantum procedure for preparing the truncated dual q-ary lattice Gaussian with a quadratic reduction in the sampling complexity. The truncation radius is chosen so that the truncated distribution is negligibly close to the full lattice Gaussian in total variation distance. Substituting this sampler into the dual attack framework results in reduced overall attack-cost estimates. Compared with Pouly and Shen's modern dual attack under the same parameter choices, our estimates reduce the attack cost by 9, 4, and 13 bits for Kyber-512, Kyber-768, and Kyber-1024, respectively. We also report the corresponding estimates with modulus switching. Finally, by replacing the Markov chain Monte Carlo (MCMC) sampler with the QRS algorithm, we achieve a similar quadratic speedup in the GPV signing process.
Although rather recent, lattice-based cryptography has stood out on numerous points, be it by the variety of constructions that it allows, by its expected resistance to quantum computers, of by its efficiency when instantiated on some classes of lattices. One of the most powerful tools of lattice-based cryptography is Gaussian sampling. At a high level, it allows to prove the knowledge of a particular lattice basis without disclosing any information about this basis. It allows to realize a wide array of cryptosystems. Somewhat surprisingly, few practical instantiations of such schemes are realized, and the algorithms which perform Gaussian sampling are seldom studied. The goal of this thesis is to fill the gap between the theory and practice of Gaussian sampling. First, we study and improve the existing algorithms, byboth a statistical analysis and a geometrical approach. We then exploit the structures underlying many classes of lattices and apply the ideas of the fast Fourier transform to a Gaussian sampler, allowing us to reach a quasilinearcomplexity instead of quadratic. Finally, we use Gaussian sampling in practice to instantiate a signature scheme and an identity-based encryption scheme. The first one yields signatures that are the most compact currently obtained in lattice-based cryptography, and the second one allows encryption and decryption that are about one thousand times faster than those obtained with a pairing-based counterpart on elliptic curves.
With the emergence of quantum computers, traditional digital signature schemes based on problems such as large integer solutions and discrete logarithms will no longer be secure, and it is urgent to find effective digital signature schemes that can resist quantum attacks. Lattice cryptography has the advantages of computational simplicity and high security. In this paper, we propose an identity-based digital signature scheme based on the rejection sampling algorithm. Unlike most schemes that use a common Gaussian distribution, this paper uses a bimodal Gaussian distribution, which improves efficiency. The identity-based signature scheme is more convenient for practical application than the traditional certificate-based signature scheme.
The security of classical public-key cryptosystems, which operate based on the computational intractability of integer factorization and discrete logarithm problems, is profoundly threatened by the rapid development of quantum computing. Post-Quantum Cryptography (PQC) has been proposed to improve security against quantum attacks. Lattice-based cryptography is widely regarded as one of the most promising PQC method because of its proven security, efficient implementation, and functional versatility, and it has achieved significant progress in both algorithmic design and engineering implementation in recent years. This paper presents a systematic survey of the status of research on lattice-based cryptographic algorithms. First, the fundamental theory of lattices and their core hard problems are discussed. Next, the technical characteristics and performance of encryption and key encapsulation mechanisms, digital signature schemes, and key exchange protocols constructed based on lattice hard problems are reviewed and compared. Subsequently, the principles and optimization paths of two key technologies for lattice cryptography implementation, namely polynomial multiplication using the fast Number Theoretic Transform (NTT) and pre-image sampling algorithms, are discussed. Finally, considering the PQC standardization process of the National Institute of Standards and Technology (NIST), an outlook on future research directions for lattice-based cryptography is presented. The research directions include the development of more "succinct" fundamental hard problems, strengthening security proofs, improving algorithm efficiency, and countering novel attacks. This review serves as a reference for promoting the practical deployment and further research of lattice-based cryptography.
Digital signatures and encryption schemes constitute arguably an integral part of cryptographic schemes with the goal to meet the security needs of present and future private and business applications. However, almost all public key cryptosystems applied in practice are put at risk due to its vulnerability to quantum attacks as a result of Shor's quantum algorithm. The magnitude of economic and social impact is tremendous inherently asking for alternatives replacing classical schemes in case large-scale quantum computers are built. Lattice-based cryptography emerged as a powerful candidate attracting lots of attention not only due to its conjectured resistance against quantum attacks, but also because of its unique security guarantee to provide worst-case hardness of average-case instances. Hence, the requirement of imposing further assumptions on the hardness of randomly chosen instances disappears, resulting in more efficient instantiations of cryptographic schemes. The best known lattice attack algorithms run in exponential time. \nIn this thesis we contribute to a smooth transition into a world with practically efficient lattice-based cryptographic schemes. This is indeed accomplished by designing new algorithms and cryptographic schemes as well as improving existing ones. Our contributions are threefold. \nFirst, we construct new encryption schemes that fully exploit the error term in LWE instances. To this end, we introduce a novel computational problem that we call Augmented LWE (A-LWE), differing from the original LWE problem only in the way the error term is produced. In fact, we embed arbitrary data into the error term without changing the target distributions. Following this, we prove that A-LWE instances are indistinguishable from LWE samples. This allows to build powerful encryption schemes on top of the A-LWE problem that are simple in its representations and efficient in practice while encrypting huge amounts of data realizing message expansion factors close to 1. This improves, to our knowledge, upon all existing encryption schemes. Due to the versatility of the error term, we further add various security features such as CCA and RCCA security or even plug lattice-based signatures into parts of the error term, thus providing an additional mechanism to authenticate encrypted data. Based on the methodology to embed arbitrary data into the error term while keeping the target distributions, we realize a novel CDT-like discrete Gaussian sampler that beats the best known samplers such as Knuth-Yao or the standard CDT sampler in terms of running time. At run time the table size amounting to 44 elements is constant for every discrete Gaussian parameter and the total space requirements are exactly as large as for the standard CDT sampler. Further results include a very efficient inversion algorithm for ring elements in special classes of cyclotomic rings. In fact, by use of the NTT it is possible to efficiently check for invertibility and deduce a representation of the corresponding unit group. Moreover, we generalize the LWE inversion algorithm for the trapdoor candidate of Micciancio and Peikert from power of two moduli to arbitrary composed integers using a different approach. \nIn the second part of this thesis, we present an efficient trapdoor construction for ideal lattices and an associated description of the GPV signature scheme. Furthermore, we improve the signing step using a different representation of the involved perturbation matrix leading to enhanced memory usage and running times. Subsequently, we introduce an advanced compression algorithm for GPV signatures, which previously suffered from huge signature sizes as a result of the construction or due to the requirement of the security proof. We circumvent this problem by introducing the notion of public and secret randomness for signatures. In particular, we generate the public portion of a signature from a short uniform random seed without violating the previous conditions. This concept is subsequently transferred to the multi-signer setting which increases the efficiency of the compression scheme in presence of multiple signers. Finally in this part, we propose the first lattice-based sequential aggregate signature scheme that enables a group of signers to sequentially generate an aggregate signature of reduced storage size such that the verifier is still able to check that each signer indeed signed a message. This approach is realized based on lattice-based trapdoor functions and has many application areas such as wireless sensor networks. \nIn the final part of this thesis, we extend the theoretical foundations of lattices and propose new representations of lattice problems by use of Cauchy integrals. Considering lattice points as simple poles of some complex functions allows to operate on lattice points via Cauchy integrals and its generalizations. For instance, we can deduce for the one-dimensional and two-dimensional case simple expressions for the number of lattice points inside a domain using trigonometric or elliptic functions.
Lattices are very important objects in the effort to construct cryptographic primitives that are secure against quantum attacks. A central problem in the study of lattices is that of finding the shortest non-zero vector in the lattice. Asymptotically, sieving is the best known technique for solving the shortest vector problem, however, sieving requires memory exponential in the dimension of the lattice. As a consequence, enumeration algorithms are often used in place of sieving due to their linear memory complexity, despite their super-exponential runtime. In this work, we present a heuristic quantum sieving algorithm that has memory complexity polynomial in the size of the length of the sampled vectors at the initial step of the sieve. In other words, unlike most sieving algorithms, the memory complexity of our algorithm does not depend on the number of sampled vectors at the initial step of the sieve.