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IET Information Security

Fully homomorphic encryption based on the ring learning with rounding problem

Fucai Luo, Fuqun Wang, Kunpeng Wang, Kefei Chen

Published Jul 17, 2019• 8 citations
Publisher

Abstract

Almost all existing well‐known fully homomorphic encryption (FHE) schemes, which are based on either the learning with errors (LWE) or the ring LWE problem, require expensive Gaussian noise sampling. In this study, the authors propose an FHE scheme based on the ring learning with rounding (RLWR) problem. The learning with rounding (LWR) problem was proposed as a deterministic variant of LWE, while the RLWR is a variant of LWR. Sampling an LWR instance does not require Gaussian noise sampling process, and neither does an RLWR instance. Thus, our FHE scheme can be instantiated without the need for Gaussian noise sampling. To implement homomorphic operations, we devise a specific relinearisation method. Furthermore, we also prove that our RLWR‐based FHE scheme is IND‐CPA secure under RLWR assumption.

DOI
10.1049/iet-ifs.2018.5427

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Almost all existing well‐known fully homomorphic encryption (FHE) schemes, which are based on either the learning with errors (LWE) or the ring LWE problem, require expensive Gaussian noise sampling. In this study, the authors propose an FHE scheme based on the ring learning with rounding (RLWR) problem. The learning with rounding (LWR) problem was proposed as a deterministic variant of LWE, while the RLWR is a variant of LWR. Sampling an LWR instance does not require Gaussian noise sampling process, and neither does an RLWR instance. Thus, our FHE scheme can be instantiated without the need for Gaussian noise sampling. To implement homomorphic operations, we devise a specific relinearisation method. Furthermore, we also prove that our RLWR‐based FHE scheme is IND‐CPA secure under RLWR assumption.
Very recently, Costache and Smart proposed a fully homomorphic encryption (FHE) scheme based on the Learning with Rounding (LWR) problem, which removes the noise (typically, Gaussian noise) sampling needed in the previous lattices-based FHEs. But their scheme did not work, since the noise of homomorphic multiplication is complicated and large, which leads to failure of decryption. More specifically, they chose LWR instances as a public key and the private key therein as a secret key and then used the tensor product to implement homomorphic multiplication, which resulted in a tangly modulus problem. Recall that there are two moduli in the LWR instances, and then the moduli will tangle together due to the tensor product. Inspired by their work, we built the first workable LWR-based FHE scheme eliminating the tangly modulus problem by cleverly adopting the celebrated approximate eigenvector method proposed by Gentry et al. at Crypto 2013. Roughly speaking, we use a specific matrix multiplication to perform the homomorphic multiplication, hence no tangly modulus problem. Furthermore, we also extend the LWR-based FHE scheme to the multikey setting using the tricks used to construct LWE-based multikey FHE by Mukherjee and Wichs at Eurocrypt 2016. Our LWR-based multikey FHE construction provides an alternative to the existing multikey FHEs and can also be applied to multiparty computation with higher efficiency.
The Learning with Errors problem (LWE) and its variants are among the most popular assumptions underlying lattice-based cryptography. The Learning with Rounding problem (LWR) can be thought of as a deterministic variant of LWE. In this work, we present a thorough study of Somewhat Homomorphic Encryption schemes based on Ring-LWR that are the analogue of the Ring-LWE-based BFV scheme. Our main contribution is to present two new schemes, in the LPR and Regev paradigms, and give a thorough analysis of their security (provable and concrete). The technical tools we developed in the process may be of independent interest to the community. Our schemes inherit the many benefits of being based on LWR, including avoiding the need for expensive Gaussian sampling and improved ciphertext size. Indeed, we give a detailed comparison showing that our schemes marginally outperform the BFV scheme in terms of ciphertext size. Moreover, we show that both our schemes support RNS variants. Our Regev-type scheme can be seen as an improved generalisation of the only prior work in this direction (Costache-Smart, 2017). In particular, our scheme resolves the tangled modulus issue in the Costache-Smart proposal that led to unmanageable noise growth, and achieves a factor n improvement in the size of the public key.
Fully dynamic multi-key fully homomorphic encryption (FHE) that allows an unlimited number of homomorphic operations for unconstrained parties. That is to say, it supports performing as many computational procedures on inputs (which are encrypted by an unrestricted number of parties) as needed. The existed fully dynamic multi-key FHE scheme is based on the learning with errors (LWE) problem. However, the LWE problem suffers from the intricate and laborious Gaussian sampling which extremely weakens the schemes’ efficiencies. What’s more, it has been lately revealed that Gaussian sampling creates lots of possible side-channel vulnerabilities that result in the disclosure of secret keys. The paper proposed a fully dynamic multi-key FHE that based on the learning with rounding (LWR) problem which leaves out the time-consuming Gaussian sampling required in the LWE problem while sustaining almost the same security level.
Fully homomorphic encryption (FHE) has important applications in cloud computing. However, almost all fully homomorphic encryption schemes share two common flaws that they all use large-scale secret keys and some operations are inefficient. In this paper, the 'special b' variant of the learning with errors problem (bLWE) is presented, and helps us construct the first circularly secure key switching process which can replace the key switching process and similar re-linearisation process used by the existing FHE schemes. Then, we present an efficient FHE. Compared with Brakerski's scheme, our scheme reduces L secret keys to one and is more efficient. Finally, we prove the chosen-plaintext attack (CPA) security of the fully homomorphic scheme and the circular security of key switching process in standard model under the learning with errors problem (LWE) assumption.
Fully homomorphic encryption (FHE) has important applications in cloud computing. However, almost all fully homomorphic encryption schemes share two common flaws that they all use large-scale secret keys and some operations are inefficient. In this paper, the 'special b' variant of the learning with errors problem (bLWE) is presented, and helps us construct the first circularly secure key switching process which can replace the key switching process and similar re-linearisation process used by the existing FHE schemes. Then, we present an efficient FHE. Compared with Brakerski's scheme, our scheme reduces L secret keys to one and is more efficient. Finally, we prove the chosen-plaintext attack (CPA) security of the fully homomorphic scheme and the circular security of key switching process in standard model under the learning with errors problem (LWE) assumption.
Fully Homomorphic Encryption (FHE) is a powerful encryption system in cloud computing that allows homomorphic computations on encrypted data without decrypting them. Multi-key fully homomorphic encryption (MFHE), as an extension to FHE, allows homomorphic computations on ciphertexts encrypted under different keys. However, most MFHE schemes require a Common Random/Reference String (CRS), while the few that do not are based on the Learning With Errors (LWE) problem, which means that they can only deal with single bit plaintext. Consequently, MFHE schemes based on the Ring Learning With Errors (RLWE) problem are more desirable, as they can handle polynomial plaintext. Requiring the CRS seems to weaken the semantic definition of MFHE, where all users generate their own keys independently. In this paper, we study the RLWE-based MFHE in the CRS model and propose the first RLWE-based MFHE without a CRS. To this end, we remove the CRS by designing a relinearization algorithm without a CRS. Like previous MFHE schemes, our RLWE-based MFHE without CRS has a simple 1-round threshold decryption, which implies a 3-round secure MPC protocol in the plain model from the RLWE assumption.