A New Algorithm for Solving Ring-LPN with a Reducible Polynomial

The LPN (Learning Parity with Noise) problem has recently proved to be of great importance in cryptology. A special and very useful case is the RING-LPN problem, which typically provides improved efficiency in the constructed cryptographic primitive. We present a new algorithm for solving the RING-LPN problem in the case when the polynomial used is reducible. It greatly outperforms previous algorithms for solving this problem. Using the algorithm, we can break the Lapin authentication protocol for the proposed instance using a reducible polynomial, in about 2^70 bit operations

An Improved BKW Algorithm for LWE with Applications to Cryptography and Lattices

In this paper, we study the Learning With Errors problem and its binary variant, where secrets and errors are binary or taken in a small interval. We introduce a new variant of the Blum, Kalai and Wasserman algorithm, relying on a quantization step that generalizes and fine-tunes modulus switching. In general this new technique yields a significant gain in the constant in front of the exponent in the overall complexity. We illustrate this by solving p within half a day a LWE instance with dimension n = 128, modulus $q = n^2$, Gaussian noise $\alpha = 1/(\sqrt{n/\pi} \log^2 n)$ and binary secret, using $2^{28}$ samples, while the previous best result based on BKW claims a time complexity of $2^{74}$ with $2^{60}$ samples for the same parameters. We then introduce variants of BDD, GapSVP and UniqueSVP, where the target point is required to lie in the fundamental parallelepiped, and show how the previous algorithm is able to solve these variants in subexponential time. Moreover, we also show how the previous algorithm can be used to solve the BinaryLWE problem with n samples in subexponential time $2^{(\ln 2/2+o(1))n/\log \log n}$. This analysis does not require any heuristic assumption, contrary to other algebraic approaches; instead, it uses a variant of an idea by Lyubashevsky to generate many samples from a small number of samples. This makes it possible to asymptotically and heuristically break the NTRU cryptosystem in subexponential time (without contradicting its security assumption). We are also able to solve subset sum problems in subexponential time for density $o(1)$, which is of independent interest: for such density, the previous best algorithm requires exponential time. As a direct application, we can solve in subexponential time the parameters of a cryptosystem based on this problem proposed at TCC 2010.Comment: CRYPTO 201

How Practical is Public-Key Encryption Based on LPN and Ring-LPN?

We conduct a study of public-key cryptosystems based on variants of the Learning Parity with Noise (LPN) problem. The main LPN variant in consideration was introduced by Alekhnovich (FOCS 2003), and we describe several improvements to the originally proposed scheme, inspired by similar existing variants of Regev\u27s LWE-based cryptosystem. To achieve further efficiency, we propose the first public-key cryptosystem based on the ring-LPN problem, which is a more recently introduced LPN variant that makes for substantial improvement in terms of both time and space. We also introduce a variant of this problem called the transposed Ring-LPN problem. Our public-key scheme based on this problem is even more efficient. For all cases, we compute the parameters required for various security levels in practice, given the best currently known attacks. Our conclusion is that the basic LPN-based scheme is in several respects not competitive with existing practical schemes, as the public key, ciphertexts and encryption time become very large already for 80-bit security. On the other hand, the scheme based on transposed Ring-LPN is far better in all these respects. Although the public key and ciphertexts are still larger than for, say, RSA at comparable security levels, they are not prohibitively large; moreover, for decryption, the scheme outperforms RSA for security levels of 112 bits or more. The Ring-LPN based scheme is less efficient, however. Thus, LPN-based public-key cryptography seems to be somewhat more promising for practical use than has been generally assumed so far

Two-Round Man-in-the-Middle Security from LPN

Secret-key authentication protocols have recently received a considerable amount of attention, and a long line of research has been devoted to devising efficient protocols with security based on the hardness of the learning-parity with noise (LPN) problem, with the goal of achieving low communication and round complexities, as well as highest possible security guarantees. In this paper, we construct 2-round authentication protocols that are secure against sequential man-in-the-middle (MIM) attacks with tight reductions to LPN, Field-LPN, or other problems. The best prior protocols had either loose reductions and required 3 rounds (Lyubashevsky and Masny, CRYPTO\u2713) or had a much larger key (Kiltz et al., EUROCRYPT\u2711 and Dodis et al., EUROCRYPT\u2712). Our constructions follow from a new generic deterministic and round-preserving transformation enhancing actively-secure protocols of a special form to be sequentially MIM-secure while only adding a limited amount of key material and computation

Post-Quantum Provably-Secure Authentication and MAC from Mersenne Primes

This paper presents a novel, yet efficient secret-key authentication and MAC, which provide post-quantum security promise, whose security is reduced to the quantum-safe conjectured hardness of Mersenne Low Hamming Combination (MERS) assumption recently introduced by Aggarwal, Joux, Prakash, and Santha (CRYPTO 2018). Our protocols are very suitable to weak devices like smart card and RFID tags

Better Algorithms for LWE and LWR

The Learning With Error problem (LWE) is becoming more and more used in cryptography, for instance, in the design of some fully homomorphic encryption schemes. It is thus of primordial importance to find the best algorithms that might solve this problem so that concrete parameters can be proposed. The BKW algorithm was proposed by Blum et al. as an algorithm to solve the Learning Parity with Noise problem (LPN), a subproblem of LWE. This algorithm was then adapted to LWE by Albrecht et al. In this paper, we improve the algorithm proposed by Albrecht et al. by using multidimensional Fourier transforms. Our algorithm is, to the best of our knowledge, the fastest LWE solving algorithm. Compared to the work of Albrecht et al. we greatly simplify the analysis, getting rid of integrals which were hard to evaluate in the final complexity. We also remove some heuristics on rounded Gaussians. Some of our results on rounded Gaussians might be of independent interest. Moreover, we also analyze algorithms solving LWE with discrete Gaussian noise. Finally, we apply the same algorithm to the Learning With Rounding problem (LWR) for prime q, a deterministic counterpart to LWE. This problem is getting more and more attention and is used, for instance, to design pseudorandom functions. To the best of our knowledge, our algorithm is the first algorithm applied directly to LWR. Furthermore, the analysis of LWR contains some technical results of independent interest

Optimization of LPN Solving Algorithms

In this article we focus on constructing an algorithm that automatizes the generation of LPN solving algorithms from the considered parameters. When searching for an algorithm to solve an LPN instance, we make use of the existing techniques and optimize their use. We formalize an LPN algorithm as a path in a graph G and our algorithm is searching for the optimal paths in this graph. The results bring improvements over the existing work by a factor from 2^8 to 2^{10}, i.e. we improve the results of the covering code from ASIACRYPT\u2714. Furthermore, we propose concrete practical codes and a method to find good codes

Correlated Pseudorandomness from the Hardness of Quasi-Abelian Decoding

Secure computation often benefits from the use of correlated randomness to achieve fast, non-cryptographic online protocols. A recent paradigm put forth by Boyle $\textit{et al.}$ (CCS 2018, Crypto 2019) showed how pseudorandom correlation generators (PCG) can be used to generate large amounts of useful forms of correlated (pseudo)randomness, using minimal interactions followed solely by local computations, yielding silent secure two-party computation protocols (protocols where the preprocessing phase requires almost no communication). An additional property called programmability allows to extend this to build N-party protocols. However, known constructions for programmable PCG's can only produce OLE's over large fields, and use rather new splittable Ring-LPN assumption. In this work, we overcome both limitations. To this end, we introduce the quasi-abelian syndrome decoding problem (QA-SD), a family of assumptions which generalises the well-established quasi-cyclic syndrome decoding assumption. Building upon QA-SD, we construct new programmable PCG's for OLE's over any field $\mathbb{F}_q$ with $q>2$. Our analysis also sheds light on the security of the ring-LPN assumption used in Boyle $\textit{et al.}$ (Crypto 2020). Using our new PCG's, we obtain the first efficient N-party silent secure computation protocols for computing general arithmetic circuit over $\mathbb{F}_q$ for any $q>2$.Comment: This is a long version of a paper accepted at CRYPTO'2

Better Algorithms for LWE and LWR

The Learning With Error problem (LWE) is becoming more and more used in cryptography, for instance, in the design of some fully homomorphic encryption schemes. It is thus of primordial importance to find the best algorithms that might solve this problem so that concrete parameters can be proposed. The BKW algorithm was proposed by Blum et al. as an algorithm to solve the Learning Parity with Noise problem (LPN), a subproblem of LWE. This algorithm was then adapted to LWE by Albrecht et al. In this paper, we improve the algorithm proposed by Albrecht et al. by using multidimensional Fourier transforms. Our algorithm is, to the best of our knowledge, the fastest LWE solving algorithm. Compared to the work of Albrecht et al. we greatly simplify the analysis, getting rid of integrals which were hard to evaluate in the final complexity. We also remove some heuristics on rounded Gaussians. Some of our results on rounded Gaussians might be of independent interest. Moreover, we also analyze algorithms solving LWE with discrete Gaussian noise. Finally, we apply the same algorithm to the Learning With Rounding problem (LWR) for prime q, a deterministic counterpart to LWE. This problem is getting more and more attention and is used, for instance, to design pseudorandom functions. To the best of our knowledge, our algorithm is the first algorithm applied directly to LWR. Furthermore, the analysis of LWR contains some technical results of independent interest

Faster Algorithms for Solving LPN

The LPN problem, lying at the core of many cryptographic constructions for lightweight and post-quantum cryptography, receives quite a lot attention recently. The best published algorithm for solving it at Asiacrypt 2014 improved the classical BKW algorithm by using covering codes, which claimed to marginally compromise the $80$-bit security of HB variants, LPN-C and Lapin. In this paper, we develop faster algorithms for solving LPN based on an optimal precise embedding of cascaded concrete perfect codes, in a similar framework but with many optimizations. Our algorithm outperforms the previous methods for the proposed parameter choices and distinctly break the 80-bit security bound of the instances suggested in cryptographic schemes like HB$^+$, HB$^\#$, LPN-C and Lapin