IEEE Transactions on Computers · 2023 · 54 citations · 11 references
ComputingComputer EngineeringComputer ScienceAlgorithmsCryptographyTheory Of ComputationCryptographic AlgorithmsData EncryptionHomomorphic EncryptionInformation-theoretic CryptographyLattice-based CryptographyFully Homomorphic EncryptionLeveled Homomorphic EncryptionNoise Management
Homomorphic Encryption (HE) makes it possible to compute on encrypted data without decryption. In lattice-based HE, a ciphertext contains noise, which accumulates along with homomorphic computations. Bootstrapping refreshes the noise and it is possible to perform arbitrary-depth computations on HE with bootstrapping, which we call Fully Homomorphic Encryption (FHE). In this article, we propose a new general bootstrapping technique for RLWE-based schemes and its practical instantiation for FHE. It can be applied to all three RLWE-based leveled FHE schemes: Brakerski-Gentry-Vaikuntanathan (BGV), Brakerski/Fan-Vercauteren (BFV), and Cheon-Kim-Kim-Song (CKKS) with minor deviations in the algorithms. Our new construction of bootstrapping extracts a noiseless ciphertext for a part of the input, scales it, and finally removes it. In contrast with previous bootstrapping algorithms, the proposed method consumes only 1–2 levels and uses smaller parameters. For BGV and BFV, our new bootstrapping does not have any restrictions on a plaintext modulus unlike typical cases of the previous methods. The error introduced by our approach for CKKS is comparable to a rescaling error, allowing us to preserve a large amount of precision after bootstrapping.
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Fully homomorphic encryption using ideal lattices
Craig Gentry · 2009 · 6.6K citations
On lattices, learning with errors, random linear codes, and cryptography
Oded Regev · Journal of the ACM · 2009 · 2.2K citations
TFHE: Fast Fully Homomorphic Encryption Over the Torus
Ilaria Chillotti, Nicolas Gama, Mariya Georgieva et al. · Journal of Cryptology · 2019 · 915 citations · Full text