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Fully homomorphic encryption based on the ring learning with rounding problem

Fucai Luo, Fuqun Wang, Kunpeng Wang, Kefei Chen

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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.

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What this paper is about

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.

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Available 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.

Key concepts: Learning with errors, Homomorphic encryption, Rounding, Computer science, Scheme (mathematics), Encryption, Ring (chemistry), Gaussian noise

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