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Fully homomorphic encryption based on the ring learning with rounding problem

机译:基于带舍入问题的环学习的全同态加密

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摘要

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.
机译:几乎所有现有的基于错误学习(LWE)或环形LWE问题的众所周知的全同态加密(FHE)方案都需要昂贵的高斯噪声采样。在这项研究中,作者提出了一种基于环学习与舍入(RLWR)问题的FHE方案。舍入学习(LWR)问题被建议作为LWE的确定性变体,而RLWR是LWR的变体。对LWR实例进行采样不需要高斯噪声采样过程,而RLWR实例也不需要。因此,可以实例化我们的FHE方案,而无需进行高斯噪声采样。为了实现同态运算,我们设计了一种特定的线性化方法。此外,我们还证明了在RLWR假设下,基于RLWR的FHE方案是IND-CPA安全的。

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