Frodo: Take off the ring! Practical, quantum-secure key exchange from LWE

Lattice-based cryptography offers some of the most attractive primitives believed to be resistant to quantum computers. Following increasing interest from both companies and government agencies in building quantum computers, a number of works have proposed instantiations of practical post-quantum key exchange protocols based on hard problems in ideal lattices, mainly based on the Ring Learning With Errors (R-LWE) problem. While ideal lattices facilitate major efficiency and storage benefits over their nonideal counterparts, the additional ring structure that enables these advantages also raises concerns about the assumed difficulty of the underlying problems. Thus, a question of significant interest to cryptographers, and especially to those currently placing bets on primitives that will withstand quantum adversaries, is how much of an advantage the additional ring structure actually gives in practice. Despite conventional wisdom that generic lattices might be too slow and unwieldy, we demonstrate that LWE-based key exchange is quite practical: our constant time implementation requires around 1.3ms computation time for each party; compared to the recent NewHope R-LWE scheme, communication sizes increase by a factor of 4.7×, but remain under 12 KiB in each direction. Our protocol is competitive when used for serving web pages over TLS; when partnered with ECDSA signatures, latencies increase by less than a factor of 1.6×, and (even under heavy load) server throughput only decreases by factors of 1.5× and 1.2× when serving typical 1 KiB and 100 KiB pages, respectively. To achieve these practical results, our protocol takes advantage of several innovations. These include techniques to optimize communication bandwidth, dynamic generation of public parameters (which also offers additional security against backdoors), carefully chosen error distributions, and tight security parameters

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

COSAC: COmpact and Scalable Arbitrary-Centered Discrete Gaussian Sampling over Integers

The arbitrary-centered discrete Gaussian sampler is a fundamental subroutine in implementing lattice trapdoor sampling algorithms. However, existing approaches typically rely on either a fast implementation of another discrete Gaussian sampler or pre-computations with regards to some specific discrete Gaussian distributions with fixed centers and standard deviations. These approaches may only support sampling from standard deviations within a limited range, or cannot efficiently sample from arbitrary standard deviations determined on-the-fly at run-time. In this paper, we propose a compact and scalable rejection sampling algorithm by sampling from a continuous normal distribution and performing rejection sampling on rounded samples. Our scheme does not require pre-computations related to any specific discrete Gaussian distributions. Our scheme can sample from both arbitrary centers and arbitrary standard deviations determined on-the-fly at run-time. In addition, we show that our scheme only requires a low number of trials close to 2 per sample on average, and our scheme maintains good performance when scaling up the standard deviation. We also provide a concrete error analysis of our scheme based on the Renyi divergence. We implement our sampler and analyse its performance in terms of storage and speed compared to previous results. Our sampler\u27s running time is center-independent and is therefore applicable to implementation of convolution-style lattice trapdoor sampling and identity-based encryption resistant against timing side-channel attacks

An erf Analog for Discrete Gaussian Sampling

Most of the current lattice-based cryptosystems rely on finding Gaussian Samples from a lattice that are close to a given target. To that end, two popular distributions have been historically defined and studied: the Rounded Gaussian distribution and the Discrete Gaussian distribution. The first one is nearly trivial to sample: simply round the coordinates of continuous Gaussian samples to their nearest integer. Unfortunately, the security of resulting cryptosystems are not as well understood. In the opposite, the second distribution is only implicitly defined by a restriction of the support of the continuous Gaussian distribution to the discrete lattice points. Thus, algorithms to achieve such distribution are more involved, even in dimension one. The justification for exerting this computational effort is that the resulting lattice-based cryptographic schemes are validated by rigorous security proofs, often by leveraging the fact that the distribution is radial and discrete Gaussians behave well under convolutions, enabling arithmetic between samples, as well as decomposition across dimensions. In this work, we unify both worlds. We construct out of infinite series, the cumulative density function of a new continuous distribution that acts as surrogate for the cumulative distribution of the discrete Gaussian. If $\mu$ is a center and $x$ a sample of this distribution, then rounding $\mu+x$ yields a faithful Discrete Gaussian sample. This new sampling algorithm naturally splits into a pre-processing/offline phase and a very efficient online phase. The online phase is simple and has a trivial constant time implementation. Modulo the offline phase, our algorithm offers both the efficiency of rounding and the security guarantees associated with discrete Gaussian sampling

Isochronous Gaussian Sampling: From Inception to Implementation

Gaussian sampling over the integers is a crucial tool in lattice-based cryptography, but has proven over the recent years to be surprisingly challenging to perform in a generic, efficient and provable secure manner. In this work, we present a modular framework for generating discrete Gaussians with arbitrary center and standard deviation. Our framework is extremely simple, and it is precisely this simplicity that allowed us to make it easy to implement, provably secure, portable, efficient, and provably resistant against timing attacks. Our sampler is a good candidate for any trapdoor sampling and it is actually the one that has been recently implemented in the Falcon signature scheme. Our second contribution aims at systematizing the detection of implementation errors in Gaussian samplers. We provide a statistical testing suite for discrete Gaussians called SAGA (Statistically Acceptable GAussian). In a nutshell, our two contributions take a step towards trustable and robust Gaussian sampling real-world implementations

Circuit-ABE from LWE: Unbounded Attributes and Semi-adaptive Security

We construct an LWE-based key-policy attribute-based encryption (ABE) scheme that supports attributes of unbounded polynomial length. Namely, the size of the public parameters is a fixed polynomial in the security parameter and a depth bound, and with these fixed length parameters, one can encrypt attributes of arbitrary length. Similarly, any polynomial size circuit that adheres to the depth bound can be used as the policy circuit regardless of its input length (recall that a depth d circuit can have as many as 2d inputs). This is in contrast to previous LWE-based schemes where the length of the public parameters has to grow linearly with the maximal attribute length. We prove that our scheme is semi-adaptively secure, namely, the adversary can choose the challenge attribute after seeing the public parameters (but before any decryption keys). Previous LWE-based constructions were only able to achieve selective security. (We stress that the “complexity leveraging” technique is not applicable for unbounded attributes). We believe that our techniques are of interest at least as much as our end result. Fundamentally, selective security and bounded attributes are both shortcomings that arise out of the current LWE proof techniques that program the challenge attributes into the public parameters. The LWE toolbox we develop in this work allows us to delay this programming. In a nutshell, the new tools include a way to generate an a-priori unbounded sequence of LWE matrices, and have fine-grained control over which trapdoor is embedded in each and every one of them, all with succinct representation.National Science Foundation (U.S.) (Award CNS-1350619)National Science Foundation (U.S.) (Grant CNS-1413964)United States-Israel Binational Science Foundation (Grant 712307

Post-quantum key exchange - a new hope

In 2015, Bos, Costello, Naehrig, and Stebila (IEEE Security & Privacy 2015) proposed an instantiation of Ding\u27s ring-learning-with-errors (Ring-LWE) based key-exchange protocol (also including the tweaks proposed by Peikert from PQCrypto 2014), together with an implementation integrated into OpenSSL, with the affirmed goal of providing post-quantum security for TLS. In this work we revisit their instantiation and stand-alone implementation. Specifically, we propose new parameters and a better suited error distribution, analyze the scheme\u27s hardness against attacks by quantum computers in a conservative way, introduce a new and more efficient error-reconciliation mechanism, and propose a defense against backdoors and all-for-the-price-of-one attacks. By these measures and for the same lattice dimension, we more than double the security parameter, halve the communication overhead, and speed up computation by more than a factor of 8 in a portable C implementation and by more than a factor of 27 in an optimized implementation targeting current Intel CPUs. These speedups are achieved with comprehensive protection against timing attacks

Threshold Raccoon: Practical Threshold Signatures from Standard Lattice Assumptions

Threshold signatures improve both availability and security of digital signatures by splitting the signing key into $N$ shares handed out to different parties. Later on, any subset of at least $T$ parties can cooperate to produce a signature on a given message. While threshold signatures have been extensively studied in the pre-quantum setting, they remain sparse from quantum-resilient assumptions. We present the first efficient lattice-based threshold signatures with signature size 13 KiB and communication cost 40 KiB per user, supporting a threshold size as large as 1024 signers. We provide an accompanying high performance implementation. The security of the scheme is based on the same assumptions as Dilithium, a signature recently selected by NIST for standardisation which, as far as we know, cannot easily be made threshold efficiently. All operations used during signing are due to symmetric primitives and simple lattice operations; in particular our scheme does not need heavy tools such as threshold fully homomorphic encryption or homomorphic trapdoor commitments as in prior constructions. The key technical idea is to use one-time additive masks to mitigate the leakage of the partial signing keys through partial signatures

Sharper Bounds in Lattice-Based Cryptography using the Rényi Divergence

The Rényi divergence is a measure of divergence between distributions. It has recently found several applications in lattice-based cryptography. The contribution of this paper is twofold. First, we give theoretic results which renders it more efficient and easier to use. This is done by providing two lemmas, which give tight bounds in very common situations { for distributions that are tailcut or have a bounded relative error. We then connect the Rényi divergence to the max-log distance. This allows the Rényi divergence to indirectly benefit from all the advantages of a distance. Second, we apply our new results to five practical usecases. It allows us to claim 256 bits of security for a floating-point precision of 53 bits, in cases that until now either required more than 150 bits of precision or were limited to 100 bits of security: rejection sampling, trapdoor sampling (61 bits in this case) and a new sampler by Micciancio and Walter. We also propose a new and compact approach for table-based sampling, and squeeze the standard deviation of trapdoor samplers by a factor that provides a gain of 30 bits of security in practice