17 research outputs found

    Middle-Products of Skew Polynomials and Learning with Errors

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    We extend the middle product to skew polynomials, which we use to define a skew middle-product Learning with Errors (LWE) variant. We also define a skew polynomial LWE problem, which we connect to Cyclic LWE (CLWE), a variant of LWE in cyclic division algebras. We then reduce a family of skew polynomial LWE problems to skew middle-product LWE, for a family which includes the structures found in CLWE. Finally, we give an encryption scheme and demonstrate its IND-CPA security, assuming the hardness of skew middle-product LWE

    Practical MP-LWE-based encryption balancing security-risk vs. efficiency

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    Middle-Product Learning With Errors (MP-LWE) is a variant of the LWE problem introduced at CRYPTO 2017 by Rosca et al [RSSS17]. Asymptotically, the theoretical results of [RSSS17] suggest that MP-LWE gives lattice-based public-key cryptosystems offering a ‘security-risk vs. efficiency’ trade-off: higher performance than cryptosystems based on unstructured lattices (LWE problem) and lower risk than cryptosystems based on structured lattices (Polynomial/Ring LWE problem). However, although promising in theory, [RSSS17] left the practical implications of MP-LWE for lattice-based cryptography unclear. In this paper, we show how to build practical public-key cryptosystems with strong security guarantees based on MP-LWE. On the implementation side, we present optimised fast algorithms for computing the middle-product operation over polynomial rings Zq[x]Z_q[x], the dominant computation for MP-LWE-based cryptosystems. On the security side, we show how to obtain a nearly tight security proof for MP-LWE from the hardest Polynomial LWE problem over a large family of rings, improving on the loose reduction of [RSSS17]. We also show and analyze an optimised cryptanalysis of MP-LWE that narrows the complexity gap to the above security proof. To evaluate the practicality of MP-LWE, we apply our results to construct, implement and optimise parameters for a practical MP-LWE-based public-key cryptosystem, Titanium, and compare its benchmarks to other lattice-based systems. Our results show that MP-LWE offers a new ‘security-risk vs. efficiency’ trade-off in lattice-based cryptography in practice, not only asymptotically in theory

    Lattice Trapdoors and IBE from Middle-Product LWE

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    Middle-product learning with errors (MP-LWE) was recently introduced by Rosca, Sakzad, Steinfeld and Stehlé (CRYPTO 2017) as a way to combine the efficiency of Ring-LWE with the more robust security guarantees of plain LWE. While Ring-LWE is at the heart of efficient lattice-based cryptosystems, it involves the choice of an underlying ring which is essentially arbitrary. In other words, the effect of this choice on the security of Ring-LWE is poorly understood. On the other hand, Rosca et al. showed that a new LWE variant, called MP-LWE, is as secure as Polynomial-LWE (another variant of Ring-LWE) over any of a broad class of number fields. They also demonstrated the usefulness of MP-LWE by constructing an MP-LWE based public-key encryption scheme whose efficiency is comparable to Ring-LWE based public-key encryption. In this work, we take this line of research further by showing how to construct Identity-Based Encryption (IBE) schemes that are secure under a variant of the MP-LWE assumption. Our IBE schemes match the efficiency of Ring-LWE based IBE, including a scheme in the random oracle model with keys and ciphertexts of size O~(n)\tilde{O}(n) (for nn-bit identities). We construct our IBE scheme following the lattice trapdoors paradigm of [Gentry, Peikert, and Vaikuntanathan, STOC\u2708]; our main technical contributions are introducing a new leftover hash lemma and instantiating a new variant of lattice trapdoors compatible with MP-LWE. This work demonstrates that the efficiency/security tradeoff gains of MP-LWE can be extended beyond public-key encryption to more complex lattice-based primitives

    Contributions to Lattice–based Cryptography

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    Post–quantum cryptography (PQC) is a new and fast–growing part of Cryptography. It focuses on developing cryptographic algorithms and protocols that resist quantum adversaries (i.e., the adversaries who have access to quantum computers). To construct a new PQC primitive, a designer must use a mathematical problem intractable for the quantum adversary. Many intractability assumptions are being used in PQC. There seems to be a consensus in the research community that the most promising are intractable/hard problems in lattices. However, lattice–based cryptography still needs more research to make it more efficient and practical. The thesis contributes toward achieving either the novelty or the practicality of lattice– based cryptographic systems

    NTRU-LPR IND-CPA: A New Ideal Lattices-based Scheme

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    In this paper, we propose NTRU-LPR IND-CPA, a new secure scheme based on the decisional variant of Bounded Distance Decoding problem over rings (DR-BDD). This scheme is IND-CPA secure and has two KEM variants IND-CCA2 secure in the random oracle model. NTRU-LPR IND-CPA is similar to NTRU LPRime and LPR Cryptosystem. NTRU-LPR IND-CPA does not have a problem of decryption failures. Our polynomial ring can be any ring of the form Z[x]/(q,f(x))\mathbb{Z}[x]/(q,f(x)), where ff is a polynomial of degree nn and qq is an integer. Relatively to the DR-BDD problem, we propose to use square-free polynomials and such polynomials include f(x)=xn−x−1f(x)=x^n-x-1 (as in NTRU LPRime) and f(x)=xn−1f(x)=x^n-1 (as in NTRU). To avoid some weaknesses in Ring-LWE or NTRU-like schemes (Meet-in-the-middle attack, Hybrid attack, Weak keys, etc.), we do not use sparse polynomials or inversion of polynomials. Furthermore, to avoid backdoors, all polynomials in our scheme can be generated by hash functions. We also give a short comparative analysis between our new scheme and some proposals of the NIST Post-Quantum call (November 2017)

    Learning with Errors over Group Rings Constructed by Semi-direct Product

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    The Learning with Errors (LWE) problem has been widely utilized as a foundation for numerous cryptographic tools over the years. In this study, we focus on an algebraic variant of the LWE problem called Group ring LWE (GR-LWE). We select group rings (or their direct summands) that underlie specific families of finite groups constructed by taking the semi-direct product of two cyclic groups. Unlike the Ring-LWE problem described in \cite{lyubashevsky2010ideal}, the multiplication operation in the group rings considered here is non-commutative. As an extension of Ring-LWE, it maintains computational hardness and can be potentially applied in many cryptographic scenarios. In this paper, we present two polynomial-time quantum reductions. Firstly, we provide a quantum reduction from the worst-case shortest independent vectors problem (SIVP) in ideal lattices with polynomial approximate factor to the search version of GR-LWE. This reduction requires that the underlying group ring possesses certain mild properties; Secondly, we present another quantum reduction for two types of group rings, where the worst-case SIVP problem is directly reduced to the (average-case) decision GR-LWE problem. The pseudorandomness of GR-LWE samples guaranteed by this reduction can be consequently leveraged to construct semantically secure public-key cryptosystems.Comment: 45 page

    Middle-Product Learning with Rounding Problem and its Applications

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    At CRYPTO 2017, Rosca et al. introduce a new variant of the Learning With Errors (LWE) problem, called the Middle-Product LWE (MP-LWE). The hardness of this new assumption is based on the hardness of the Polynomial LWE (P-LWE) problem parameterized by a set of polynomials, making it more secure against the possible weakness of a single defining polynomial. As a cryptographic application, they also provide an encryption scheme based on the MP-LWE problem. In this paper, we propose a deterministic variant of their encryption scheme, which does not need Gaussian sampling and is thus simpler than the original one. Still, it has the same quasi-optimal asymptotic key and ciphertext sizes. The main ingredient for this purpose is the Learning With Rounding (LWR) problem which has already been used to derandomize LWE type encryption. The hardness of our scheme is based on a new assumption called Middle-Product Computational Learning With Rounding, an adaption of the computational LWR problem over rings, introduced by Chen et al. at ASIACRYPT 2018. We prove that this new assumption is as hard as the decisional version of MP-LWE and thus benefits from worst-case to average-case hardness guarantees

    Variants of LWE: Reductions, Attacks and a Construction

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    Usability of structured lattices for a post-quantum cryptography: practical computations, and a study of some real Kummer extensions

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    Lattice-based cryptography is an excellent candidate for post-quantum cryptography, i.e. cryptosystems which are resistant to attacks run on quantum computers. For efficiency reason, most of the constructions explored nowadays are based on structured lattices, such as module lattices or ideal lattices. The security of most constructions can be related to the hardness of retrieving a short element in such lattices, and one does not know yet to what extent these additional structures weaken the cryptosystems. A related problem – which is an extension of a classical problem in computational number theory – called the Short Principal Ideal Problem (or SPIP), consists of finding a short generator of a principal ideal. Its assumed hardness has been used to build some cryptographic schemes. However it has been shown to be solvable in quantum polynomial time over cyclotomic fields, through an attack which uses the Log-unit lattice of the field considered. Later, practical results showed that multiquadratic fields were also weak to this strategy. The main general question that we study in this thesis is To what extent can structured lattices be used to build a post-quantum cryptography
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