On error distributions in ring-based LWE

Since its introduction in 2010 by Lyubashevsky, Peikert and Regev, the ring learning with errors problem (ring-LWE) has become a popular building block for cryptographic primitives, due to its great versatility and its hardness proof consisting of a (quantum) reduction from ideal lattice problems. But, for a given modulus q and degree n number field K, generating ring-LWE samples can be perceived as cumbersome, because the secret keys have to be taken from the reduction mod q of a certain fractional ideal O-K(V) subset of K called the codifferent or 'dual', rather than from the ring of integers O-K itself. This has led to various non-dual variants of ring-LWE, in which one compensates for the non-duality by scaling up the errors. We give a comparison of these versions, and revisit some unfortunate choices that have been made in the recent literature, one of which is scaling up by vertical bar Delta(K)vertical bar(1/2n) with Delta(K) the discriminant of K. As a main result, we provide, for any epsilon > 0, a family of number fields K for which this variant of ring-LWE can be broken easily as soon as the errors are scaled up by vertical bar Delta(K)vertical bar((1-epsilon)/n)

Efficiently processing complex-valued data in homomorphic encryption

We introduce a new homomorphic encryption scheme that is natively capable of computing with complex numbers. This is done by generalizing recent work of Chen, Laine, Player and Xia, who modified the Fan–Vercauteren scheme by replacing the integral plaintext modulus t by a linear polynomial X − b. Our generalization studies plaintext moduli of the form Xm + b. Our construction significantly reduces the noise growth in comparison to the original FV scheme, so much deeper arithmetic circuits can be homomorphically executed

Integer Functions Suitable for Homomorphic Encryption over Finite Fields

Fully Homomorphic Encryption (FHE) gives the ability to evaluate any function over encrypted data. However, despite numerous improvements during the last decade, the computational overhead caused by homomorphic computations is still very important. As a consequence, optimizing the way of performing the computations homomorphically remains fundamental. Several popular FHE schemes such as BGV and BFV encode their data, and thus perform their computations, in finite fields. In this work, we study and exploit algebraic relations occurring in prime characteristic allowing to speed-up the homomorphic evaluation of several functions over prime fields. More specifically we give several examples of unary functions: modulo , is power of $b$ , Hamming weight and Mod2\u27 whose homomorphic evaluation complexity over $\mathbb{F}_p$ can be reduced from the generic bound $\sqrt{2p} + \mathcal{O}(\log(p))$ homomorphic multiplications, to $\sqrt{p} + \mathcal{O}(\log(p))$, $\mathcal{O}(\log (p))$, $\mathcal{O}(\sqrt{p/\log (p)})$ and $\mathcal{O}(\sqrt{p/\log (p)})$ respectively. Additionally we provide a proof of a recent claim regarding the structure of the polynomial interpolation of the less-than bivariate function which confirms that this function can be evaluated in $2p-6$ homomorphic multiplications instead of $3p-5$ over $\mathbb{F}_p$ for $p\geq 5$

When HEAAN Meets FV: a New Somewhat Homomorphic Encryption with Reduced Memory Overhead

We demonstrate how to reduce the memory overhead of somewhat homomorphic encryption (SHE) while computing on numerical data. We design a hybrid SHE scheme that exploits the packing algorithm of the HEAAN scheme and the variant of the FV scheme by Bootland et al. The ciphertext size of the resulting scheme is 3-18 times smaller than in HEAAN to compute polynomial functions of depth 4 while packing a small number of data values. Furthermore, our scheme has smaller ciphertexts even with larger packing capacities (256-2048 values)

On Polynomial Functions Modulo pep^e and Faster Bootstrapping for Homomorphic Encryption

In this paper, we perform a systematic study of functions $f: \mathbb{Z}_{p^e} \to \mathbb{Z}_{p^e}$ and categorize those functions that can be represented by a polynomial with integer coefficients. More specifically, we cover the following properties: necessary and sufficient conditions for the existence of an integer polynomial representation; computation of such a representation; and the complete set of equivalent polynomials that represent a given function. As an application, we use the newly developed theory to speed up bootstrapping for the BGV and BFV homomorphic encryption schemes. The crucial ingredient underlying our improvements is the existence of null polynomials, i.e. non-zero polynomials that evaluate to zero in every point. We exploit the rich algebraic structure of these null polynomials to find better representations of the digit extraction function, which is the main bottleneck in bootstrapping. As such, we obtain sparse polynomials that have 50% fewer coefficients than the original ones. In addition, we propose a new method to decompose digit extraction as a series of polynomial evaluations. This lowers the time complexity from $\mathcal{O}(\sqrt{pe})$ to $\mathcal{O}(\sqrt{p}\sqrt[^4]{e})$ for digit extraction modulo $p^e$, at the cost of a slight increase in multiplicative depth. Overall, our implementation in HElib shows a significant speedup of a factor up to 2.6 over the state-of-the-art

Homomorphically counting elements with the same property

We propose homomorphic algorithms for privacy-preserving applications where we are given an encrypted dataset and we want to compute the number of elements that share a common property. We consider a two-party scenario between a client and a server, where the storage and computation is outsourced to the server. We present two new efficient methods to solve this problem by homomorphically evaluating a selection function encoding the desired property, and counting the number of elements which evaluates to the same value. Our first method programs the homomorphic computation in the style of the functional bootstrapping of TFHE and can be instantiated with essentially any homomorphic encryption scheme that operates on polynomials, like FV or BGV. Our second method relies on new homomorphic operations and ciphertext formats, and it is more suitable for applications where the number of possible inputs is much larger than the number of possible values for the property. We illustrate the feasibility of our methods by presenting a publicly available proof-of-concept implementation in C++ and using it to evaluate a heatmap function over encrypted geographic points

FINAL: Faster FHE instantiated with NTRU and LWE

The NTRU problem is a promising candidate to build efficient Fully Homomorphic Encryption (FHE). However, all the existing proposals (e.g. LTV, YASHE) need so-called `overstretched\u27 parameters of NTRU to enable homomorphic operations. It was shown by Albrecht et al. (CRYPTO 2016) that these parameters are vulnerable against subfield lattice attacks. Based on a recent, more detailed analysis of the overstretched NTRU assumption by Ducas and van Woerden (ASIACRYPT 2021), we construct two FHE schemes whose NTRU parameters lie outside the overstretched range. The first scheme is based solely on NTRU and demonstrates competitive performance against the state-of-the-art FHE schemes including TFHE. Our second scheme, which is based on both the NTRU and LWE assumptions, outperforms TFHE with a 28% faster bootstrapping and 45% smaller bootstrapping and key-switching keys

Labeled PSI from Homomorphic Encryption with Reduced Computation and Communication

It is known that fully homomorphic encryption (FHE) can be used to build efficient (labeled) Private Set Intersection protocols in the unbalanced setting, where one of the sets is much larger than the other (Chen et al. (CCS\u2717, CCS\u2718)). In this paper we demonstrate multiple algorithmic improvements upon these works. In particular, our protocol has an asymptotically better computation cost, requiring only $O(\sqrt{|X|})$ homomorphic multiplications, and communication complexity sublinear in the larger set size $|X|$. We demonstrate that our protocol is significantly better than that of Chen et al. (CCS\u2718) for many practical parameters, especially in terms of online communication cost. For example, when intersecting $2^{28}$ and $2048$ item sets, our protocol reduces the online computation time by more than 83% and communication by more than 32%. When intersecting $2^{24}$ and $4096$ item sets, our protocol reduces the online computation time by 50% and communication by 52%. Our comparison to other state-of-the-art unbalanced PSI protocols shows that our protocol has the best total communication complexity when $|X| \geq 2^{24}$. For labeled PSI our protocol also outperforms Chen et al. (CCS\u2718). When intersecting $2^{20}$ and $256$ item sets, with the larger set having associated $288$-byte labels, our protocol reduces the online computation time by more than 85% and communication by 36%. Finally, we demonstrate a modification that results in nearly constant communication cost in the larger set size $|X|$, but impractically high computation complexity on today\u27s CPUs. For example, to intersect a $210$-item set with sets of size $2^{22}$, $2^{24}$, or $2^{26}$, our proof-of-concept implementation requires only $0.76$ MB of online communication, which is more than a $24$-fold improvement over Chen et al. (CCS\u2718)

On Error Distributions in Ring-based LWE

© The Author(s) 2016. Since its introduction in 2010 by Lyubashevsky, Peikert and Regev, the ring learning with errors problem (ring-LWE) has become a popular building block for cryptographic primitives, due to its great versatility and its hardness proof consisting of a (quantum) reduction from ideal lattice problems. But, for a given modulus q and degree n number field K, generating ring-LWE samples can be perceived as cumbersome, because the secret keys have to be taken from the reduction mod q of a certain fractional ideal OVK K called the codi erent or 'dual', rather than from the ring of integers OK itself. This has led to various non-dual variants of ring-LWE, in which one compensates for the non-duality by scaling up the errors. We give a comparison of these versions, and revisit some unfortunate choices that have been made in the recent literature, one of which is scaling up by |ΔK|1/2n with ΔK the discriminant of K. As a main result, we provide, for any ϵ > 0, a family of number fields K for which this variant of ring-LWE can be broken easily as soon as the errors are scaled up by |ΔK|(1-ϵ)/n.status: publishe

Provably Weak Instances of Ring-LWE Revisited

© International Association for Cryptologic Research 2016. In CRYPTO 2015, Elias, Lauter, Ozman and Stange described an attack on the non-dual decision version of the ring learning with errors problem (RLWE) for two special families of defining polynomials, whose construction depends on the modulus q that is being used. For particularly chosen error parameters, they managed to solve nondual decision RLWE given 20 samples, with a success rate ranging from 10% to 80%. In this paper we show how to solve the search version for the same families and error parameters, using only 7 samples with a success rate of 100%. Moreover our attack works for every modulus q′ instead of the q that was used to construct the defining polynomial. The attack is based on the observation that the RLWE error distribution for these families of polynomials is very skewed in the directions of the polynomial basis. For the parameters chosen by Elias et al. the smallest errors are negligible and simple linear algebra suffices to recover the secret. But enlarging the error paremeters makes the largest errors wrap around, thereby turning the RLWE problem unsuitable for cryptographic applications. These observations also apply to dual RLWE, but do not contradict the seminal work by Lyubashevsky, Peikert and Regev.status: publishe