We give a polynomial-time quantum reduction from worst-case (ideal) lattice problems directly to decision (Ring-)LWE. This extends to decision all the worst-case hardness results that were previously known for the search version, for the same or even better parameters and with no algebraic restrictions on the modulus or number field. Indeed, our reduction is the first that works for decision Ring-LWE with any number field and any modulus.
We give a polynomial-time quantum reduction from worst-case (ideal) lattice problems directly to decision (Ring-)LWE. This extends to decision all the worst-case hardness results that were previously known for the search version, for the same or even better parameters and with no algebraic restrictions on the modulus or number field. Indeed, our reduction is the first that works for decision Ring-LWE with any number field and any modulus.
Abstract. The decision Learning With Errors problem has proven an extremely flexible foundation for devising provably secure cryptographic primitives. LWE can be expressed in terms of linear algebra over Z/qZ. This modulus q is the subject of study of the present work. When q is prime and small, or when it is exponential and composite with small factors, LWE is known to be at least as hard as standard worst-case problems over euclidean lattices (sometimes using quantum reductions). The Ring Learning With Errors problem is a structured variant of LWE allowing for more compact keys and more efficient primitives. It is known to be at least as hard as standard worst-case problems restricted to so-called ideal lattices, but under even more restrictive arithmetic conditions on q. In this work, we prove that the arithmetic form of the modulus q is irrelevant to the computational hardness of LWE and RLWE. More precisely, we show that these problems are at least as hard as standard worst-case problems on lattices, under the unique condition that q is of polynomial bit-size. This result is most useful for adapting LWE-based cryptographic constructions to the RLWE setting. Among others, this allows us to derive the first Identity-Based Encryption scheme of quasi-optimal performance proven secure under standard worst-case lattice assumptions, in the standard model. Other applications include authentication, functional encryption and traitor tracing.
The “learning with errors ” (LWE) problem is to distinguish random linear equations, which have been perturbed by a small amount of noise, from truly uniform ones. The problem has been shown to be as hard as worst-case lattice problems, and in recent years it has served as the foundation for a plethora of cryptographic applications. Unfortunately, these applications are rather inefficient due to an inherent quadratic overhead in the use of LWE. A main open question was whether LWE and its applications could be made truly efficient by exploiting extra algebraic structure, as was done for lattice-based hash functions (and related primitives). We resolve this question in the affirmative by introducing an algebraic variant of LWE called ring-LWE, and proving that it too enjoys very strong hardness guarantees. Specifically, we show that the ring-LWE distribution is pseudorandom, assuming that worst-case problems on ideal lattices are hard for polynomial-time quantum algorithms. Applications include the first truly practical lattice-based public-key cryptosystem with an efficient security reduction; moreover, many of the other applications of LWE can be made much more efficient through the use of ring-LWE. 1
Abstract. Most lattice-based cryptographic schemes are built upon the assumed hardness of the Short Integer Solution (SIS) and Learning With Errors (LWE) problems. Their efficiencies can be drastically improved by switching the hardness assumptions to the more compact Ring-SIS and Ring-LWE problems. However, this change of hardness assumptions comes along with a possible security weakening: SIS and LWE are known to be at least as hard as standard (worst-case) problems on euclidean lattices, whereas Ring-SIS and Ring-LWE are only known to be as hard as their restrictions to special classes of ideal lattices, corresponding to ideals of some polynomial rings. In this work, we define the Module-SIS and Module-LWE problems, which bridge SIS with Ring-SIS, and LWE with Ring-LWE, respectively. We prove that these average-case problems are at least as hard as standard lattice problems restricted to module lattices (which themselves generalize arbitrary and ideal lattices). As these new problems enlarge the toolbox of the lattice-based cryptographer, they could prove useful for designing new schemes. Importantly, the worst-case to average-case reductions for the module problems are (qualitatively) sharp, in the sense that there exist converse reductions. This property is not known to hold in the context of Ring-SIS/Ring-LWE: Ideal lattice problems could reveal easy without impacting the hardness of Ring-SIS/Ring-LWE. 1
Several works have characterized weak instances of the Ring-LWE problem by exploring vulnerabilities arising from the use of algebraic structures. Although these weak instances are not addressed by worst-case hardness theorems, enabling other ring instantiations enlarges the scope of possible applications and favors the diversification of security assumptions. In this work, we extend the Ring-LWE problem in lattice-based cryptography to include algebraic lattices, realized through twisted embeddings. We define the class of problems Twisted Ring-LWE, which replaces the canonical embedding by an extended form. By doing so, we allow the Ring-LWE problem to be used over maximal real subfields of cyclotomic number fields. We prove that Twisted Ring-LWE is secure by providing a security reduction from Ring-LWE to Twisted Ring-LWE in both search and decision forms. It is also shown that the twist factor does not affect the asymptotic approximation factors in the worst-case to average-case reductions. Thus, Twisted Ring-LWE maintains the consolidated hardness guarantee of Ring-LWE and increases the existing scope of algebraic lattices that can be considered for cryptographic applications. Additionally, we expand on the results of Ducas and Durmus (Public-Key Cryptography, 2012) on spherical Gaussian distributions to the proposed class of lattices under certain restrictions. As a result, sampling from a spherical Gaussian distribution can be done directly in the respective number field while maintaining its format and standard deviation when seen in Zn via twisted embeddings.
This note describes a key exchange method based on the ring-LWE (RLWE)
assumption. It builds upon several results, including Regev's
landmark quantum reduction from certain worst case lattice problems
(approx. GapSVP and SIVP) to random instances of the search variant of
a particular learning problem (LWE). It also builds on the follow on
work of Lyubashevsky, Peikert and Regev on the average case hardness
of the RLWE search variant for polynomially bounded numbers of RLWE
samples, along with novel applications of automorphism groups in
number fields for a RLWE search to decision reduction (thereby
demonstrating pseudorandomness of RLWE in these number fields).
Subsequently, these results were adopted for the construction of
Diffie-Hellman like key exchange methods by Peikert, and then by
Lindner and Peikert followed by Ding and then by Ding, Xie and Lin who
proposed efficient variants of such protocols. Subsequent work by
Peikert proposed another efficient variant, phrased as a key
encapsulation method, incorporating a low bandwidth reconciliation
technique allowing two parties to exactly agree on a uniformly
distributed secret value from noisy RLWE instances. This was followed
by a concrete instantiation with parameter sets by Bos, Costello,
Naehrig, Stebila, followed by another instantiation by Alkim, Ducas,
Poppelmann and Schwabe with the same ring polynomial but a smaller
modulus and a different reconciliation method. Unlike most other
public key cryptography based key exchange methods, it is believed
that RLWE based key exchange would remain secure in the event that an
adversary is able to build a quantum computer. This document is a
product of the Crypto Forum Research Group (CFRG).
The “learning with errors” (LWE) problem is to distinguish random linear equations, which have been perturbed by a small amount of noise, from truly uniform ones. The problem has been shown to be as hard as worst-case lattice problems, and in recent years it has served as the foundation for a plethora of cryptographic applications. Unfortunately, these applications are rather inefficient due to an inherent quadratic overhead in the use of LWE. A main open question was whether LWE and its applications could be made truly efficient by exploiting extra algebraic structure, as was done for lattice-based hash functions (and related primitives). We resolve this question in the affirmative by introducing an algebraic variant of LWE called ring-LWE , and proving that it too enjoys very strong hardness guarantees. Specifically, we show that the ring-LWE distribution is pseudorandom, assuming that worst-case problems on ideal lattices are hard for polynomial-time quantum algorithms. Applications include the first truly practical lattice-based public-key cryptosystem with an efficient security reduction; moreover, many of the other applications of LWE can be made much more efficient through the use of ring-LWE.