International Association
for Cryptologic Research

The so-called $\omega$-encoding, introduced by Goudarzi, Joux and Rivain (Asiacrypt 2018), generalizes the commonly used arithmetic encoding. By using the additionnal structure of this encoding, they proposed a masked multiplication gadget (GJR) with quasilinear (randomness and operations) complexity. A follow-up contribution by Goudarzi, Prest, Rivain and Vergnaud in this line of research appeared in TCHES 2021. The authors revisited the aforementioned multiplication gadget (GPRV), and brought the IOS security notion for refresh gadgets to allow secure composition between probing secure gadgets. In this paper, we propose a follow up on GPRV, that is, a region-probing secure arithmetic circuit masked compiler. Our contribution stems from a single Lemma, linking algebra and probing security for a wide class of circuits, further taking advantage of the algebraic structure of !-encoding, and the extension field structure of the underlying field F that was so far left unexploited. On the theoretical side, we propose a security notion for !d-masked circuits which we call Reducible-To-Independent-K-linear (RTIK). When the number of shares d is less than or equal to the degree k of F, RTIK circuits achieve region-probing security. Moreover, RTIK circuits may be composed naively and remain RTIK. We also propose a weaker version of IOS, which we call KIOS, for refresh gadgets. This notion allows to compose RTIK circuits with a randomness/security tradeoff compared to the naive composition. To substantiate our new definitions, we also provide examples of competitively efficient gadgets verifying the latter weaker security notions. Explicitly, we give 1) two refresh gadgets that use d - 1 random field elements to refresh a length d encoding, both of which are KIOS but not IOS, and 2) a multiplication gadget with bilinear multiplication complexity dlog 3 and uses d fresh random elements per run. Our compiler outperforms ISW asymptotically, but for our security proofs to hold, we do require that the number of shares d is less than or equal to the degree of F as an extension, so that there is sufficient structure to exploit.

Lattice-based blind signature schemes have been receiving some recent attention lately. Earlier efficient 3-round schemes (Asiacrypt 2010, Financial Cryptography 2020) were recently shown to have mistakes in their proofs, and fixing them turned out to be extremely inefficient and limited the number of signatures that a signer could send to less than a dozen (Crypto 2020). In this work we propose a round-optimal, 2-round lattice-based blind signature scheme which produces signatures of length 150KB. The running time of the signing protocol is linear in the maximum number signatures that can be given out, and this limits the number of signatures that can be signed per public key. Nevertheless, the scheme is still quite efficient when the number of signatures is limited to a few dozen thousand, and appears to currently be the most efficient lattice-based candidate.

We present a much-improved practical protocol, based on the hardness of Module-SIS and Module-LWE problems, for proving knowledge of a short vector $s$ satisfying $As=t\bmod q$. The currently most-efficient technique for constructing such a proof works by showing that the $\ell_\infty$ norm of $s$ is small. It creates a commitment to a polynomial vector $m$ whose CRT coefficients are the coefficients of $s$ and then shows that (1) $A\cdot \mathsf{CRT}(m)=t\bmod\,q$ and (2) in the case that we want to prove that the $\ell_\infty$ norm is at most $1$, the polynomial product $(m - 1)\cdot m\cdot(m+1)$ equals to $0$. While these schemes are already quite efficient for practical applications, the requirement of using the CRT embedding and only being naturally adapted to proving the $\ell_\infty$-norm, hinders the efficiency of this approach. In this work, we show that there is a direct and efficient way to prove that the coefficients of $s$ have a small $\ell_2$ norm which does not require an equivocation with the $\ell_\infty$ norm, nor any conversion to the CRT representation. We observe that the inner product between two vectors $ r$ and $s$ can be made to appear as a coefficient of a product (or sum of products) between polynomials which are functions of $r$ and $s$. Thus, by using a polynomial product proof system and hiding all but one coefficient, we are able to prove knowledge of the inner product of two vectors modulo $q$. Using a cheap, approximate range proof, one can then lift the proof to be over $\mathbb{Z}$ instead of $\mathbb{Z}_q$. Our protocols for proving short norms work over all (interesting) polynomial rings, but are particularly efficient for rings like $\mathbb{Z}[X]/(X^n+1)$ in which the function relating the inner product of vectors and polynomial products happens to be a ``nice'' automorphism. The new proof system can be plugged into constructions of various lattice-based privacy primitives in a black-box manner. As examples, we instantiate a verifiable encryption scheme and a group signature scheme which are more than twice as compact as the previously best solutions.

We propose a new framework for (trapdoor) sampling over lattices. Our framework can be instantiated in a number of ways. It allows for example to sample from uniform, affine and “product affine” distributions. Another salient point of our framework is that the output distributions of our samplers are perfectly indistinguishable from ideal ones, in contrast with classical samplers that are statistically indistinguishable. One caveat of our framework is that all our current instantiations entail a rather large standard deviation.

We present an improved lattice-based group signature scheme whose parameter sizes and running times are independent of the group size. The signature length in our scheme is around $200$KB, which is approximately a $3$X reduction over the previously most compact such scheme, based on any quantum-safe assumption, of del Pino et al. (CCS 2018). The improvement comes via several optimizations of some basic cryptographic components that make up group signature schemes, and we think that they will find other applications in privacy-based lattice cryptography.

The hardness of finding short vectors in ideals of cyclotomic number fields (hereafter, Ideal-SVP) can serve as a worst-case assumption for numerous efficient cryptosystems, via the average-case problems Ring-SIS and Ring-LWE. For a while, it could be assumed the Ideal-SVP problem was as hard as the analog problem for general lattices (SVP), even when considering quantum algorithms.But in the last few years, a series of works has lead to a quantum algorithm for Ideal-SVP that outperforms what can be done for general SVP in certain regimes. More precisely, it was demonstrated (under certain hypotheses) that one can find in quantum polynomial time a vector longer by a factor at most $$\alpha = \exp ({\widetilde{O}(n^{1/2})})$$ than the shortest non-zero vector in a cyclotomic ideal lattice, where n is the dimension.In this work, we explore the constants hidden behind this asymptotic claim. While these algorithms have quantum steps, the steps that impact the approximation factor $$\alpha $$ are entirely classical, which allows us to estimate it experimentally using only classical computing. Moreover, we design heuristic improvements for those steps that significantly decrease the hidden factors in practice. Finally, we derive new provable effective lower bounds based on volumetric arguments.This study allows to predict the crossover point with classical lattice reduction algorithms, and thereby determine the relevance of this quantum algorithm in any cryptanalytic context. For example we predict that this quantum algorithm provides shorter vectors than BKZ-300 (roughly the weakest security level of NIST lattice-based candidates) for cyclotomic rings of rank larger than about 24000.