Ring Packing and Amortized FHEW Bootstrapping

The FHEW fully homomorphic encryption scheme (Ducas and Micciancio, Eurocrypt 2015) offers very fast homomorphic NAND-gate computations (on encrypted data) and a relatively fast refreshing procedure that allows to homomorphically evaluate arbitrary NAND boolean circuits. Unfortunately, the refreshing procedure needs to be executed after every single NAND computation, and each refreshing operates on a single encrypted bit, greatly decreasing the overall throughput of the scheme. We give a new refreshing procedure that simultaneously refreshes n FHEW ciphertexts, at a cost comparable to a single-bit FHEW refreshing operation. As a result, the cost of each refreshing is amortized over n encrypted bits, improving the throughput for the homomorphic evaluation of boolean circuits roughly by a factor n

Faster Amortized FHEW bootstrapping using Ring Automorphisms

Amortized bootstrapping offers a way to simultaneously refresh many ciphertexts of a fully homomorphic encryption scheme, at a total cost comparable to that of refreshing a single ciphertext. An amortization method for FHEW-style cryptosystems was first proposed by (Micciancio and Sorrell, ICALP 2018), who showed that the amortized cost of bootstrapping n FHEW-style ciphertexts can be reduced from $O(n)$ basic cryptographic operations to just $O(n^{\epsilon})$, for any constant $\epsilon>0$. However, despite the promising asymptotic saving, the algorithm was rather inpractical due to a large constant (exponential in $1/\epsilon$) hidden in the asymptotic notation. In this work, we propose an alternative amortized boostrapping method with much smaller overhead, still achieving $O(n^\epsilon)$ asymptotic amortized cost, but with a hidden constant that is only linear in $1/\epsilon$, and with reduced noise growth. This is achieved following the general strategy of (Micciancio and Sorrell), but replacing their use of the Nussbaumer transform, with a much more practical Number Theoretic Transform, with multiplication by twiddle factors implemented using ring automorphisms. A key technical ingredient to do this is a new scheme switching technique proposed in this paper which may be of independent interest

Improved Circuit Synthesis with Amortized Bootstrapping for FHEW-like Schemes

In recent years, the research community has made great progress in improving techniques for privacy-preserving computation such as fully homomorphic encryption (FHE). Despite the progress, there remain open challenges, mostly in the areas of performance and usability, to further advance the adoption of these technologies. This work provides multiple contributions to improve the current state-of-the-art in both areas. More specifically, we significantly simplify the bootstrapping idea by Carpov, Izabach`ene, and Mollimard [1] for Boolean-based FHE schemes such as FHEW or TFHE, making the concept usable in practice. Based on our simplifications, we provide an easy-to-use interface for amortized bootstrapping implementing our improvements in the open-source library FHE-Deck and provide new parameter sets for multi-bit encryptions with state-of-the-art security. We build a toolset that compiles high-level code such as C++ to code that executes operations on encrypted data. For this toolset, we propose the first non-trivial FHE-specific optimizations in synthesizing privacy-preserving circuits from high-level code, namely look-up table (LUT) grouping and adder substitution. Using LUT grouping, we reduce the number of bootstrapping required by almost 35 % on average, while for adder substitution, we reduce the number of required bootstrapping by up to 80 % for certain use cases. Overall, the execution time is up to 3.8× faster using our optimizations compared to previous state-of-the-art circuit synthesis

Bootstrapping Bits with CKKS

The Cheon-Kim-Kim-Song (CKKS) fully homomorphic encryption scheme is designed to efficiently perform computations on real numbers in an encrypted state. Recently, Drucker et al. [J. Cryptol.] proposed an efficient strategy to use CKKS in a black-box manner to perform computations on binary data. In this work, we introduce several CKKS bootstrapping algorithms designed specifically for ciphertexts encoding binary data. Crucially, the new CKKS bootstrapping algorithms enable to bootstrap ciphertexts containing the binary data in the most significant bits. First, this allows to decrease the moduli used in bootstrapping, saving a larger share of the modulus budget for non-bootstrapping operations. In particular, we obtain full-slot bootstrapping in ring degree $2^{14}$ for the first time. Second, the ciphertext format is compatible with the one used in the DM/CGGI fully homomorphic encryption schemes. Interestingly, we may combine our CKKS bootstrapping algorithms for bits with the fast ring packing technique from Bae et al. [CRYPTO\u2723]. This leads to a new bootstrapping algorithm for DM/CGGI that outperforms the state-of-the-art approaches when the number of bootstraps to be performed simultaneously is in the low hundreds

Large-Plaintext Functional Bootstrapping in FHE with Small Bootstrapping Keys

Functional bootstrapping is a core technique in Fully Homomorphic Encryption (FHE). For large plaintext, to evaluate a general function homomorphically over a ciphertext, in the FHEW/TFHE approach, since the function in look-up table form is encoded in the coefficients of a test polynomial, the degree of the polynomial must be high enough to hold the entire table. This increases the bootstrapping time complexity and memory cost, as the size of bootstrapping keys and keyswitching keys need to be large accordingly. In this paper, we propose to encode the look-up table of any function in a polynomial vector, whose coefficients can hold more data. The corresponding representation of the additive group Zq used in the RGSW-based bootstrapping is the group of monic monomial permutation matrices, which integrates the permutation matrix representation used by Alperin-Sheriff and Peikert in 2014, and the monic monomial representation used in the FHEW/TFHE scheme. We make comprehensive investigation of the new representation, and propose a new bootstrapping algorithm based on it. The new algorithm has the prominent benefit of small bootstrapping key size and small key-switching key size, which leads to polynomial factor improvement in key size, in addition to constant factor improvement in run-time cost.Comment: 12 pages,under review of some journa

Constant-Size Unbounded Multi-Hop Fully Homomorphic Proxy Re-Encryption from Lattices

Proxy re-encryption is a cryptosystem that achieves efficient encrypted data sharing by allowing a proxy to transform a ciphertext encrypted under one key into another ciphertext under a different key. Homomorphic proxy re-encryption (HPRE) extends this concept by integrating homomorphic encryption, allowing not only the sharing of encrypted data but also the homomorphic computations on such data. The existing HPRE schemes, however, are limited to a single or bounded number of hops of ciphertext re-encryptions. To address this limitation, this paper introduces a novel lattice-based, unbounded multi-hop fully homomorphic proxy re-encryption (FHPRE) scheme, with constant-size ciphertexts. Our FHPRE scheme supports an unbounded number of reencryption operations and enables arbitrary homomorphic computations over original, re-encrypted, and evaluated ciphertexts. Additionally, we propose a potential application of our FHPRE scheme in the form of a non-interactive, constant-size multi-user computation system for cloud computing environments

LFHE: Fully Homomorphic Encryption with Bootstrapping Key Size Less than a Megabyte

Fully Homomorphic Encryption (FHE) enables computations to be performed on encrypted data, so one can outsource computations of confidential information to an untrusted party. Ironically, FHE requires the client to generate massive evaluation keys and transfer them to the server side where all computations are supposed to be performed. In this paper, we propose LFHE, the Light-key FHE variant of the FHEW scheme introduced by Ducas and Micciancio in Eurocrypt 2015, and its improvement TFHE scheme proposed by Chillotti et al. in Asiacrypt 2016. In the proposed scheme the client generates small packed evaluation keys, which can be transferred to the server side with much smaller communication overhead compared to the original non-packed variant. The server employs a key reconstruction technique to obtain the evaluation keys needed for computations. This approach allowed us to achieve the FHE scheme with the packed evaluation key transferring size of less than a Megabyte, which is an order of magnitude improvement compared to the best-known methods

Amortized Bootstrapping Revisited: Simpler, Asymptotically-faster, Implemented

Micciancio and Sorrel (ICALP 2018) proposed a bootstrapping algorithm that can refresh many messages at once with sublinearly many homomorphic operations per message. However, despite the attractive asymptotic cost, it is unclear if their algorithm could ever be practical, which reduces the impact of their results. In this work, we follow their general framework, but propose an amortized bootstrapping that is conceptually simpler and asymptotically cheaper. We reduce the number of homomorphic operations per refreshed message from $O(3^\rho \cdot n^{1/\rho} \cdot \log n)$ to $O(\rho \cdot n^{1/\rho})$, and the noise overhead from $\tilde{O}(n^{2 + 3 \cdot \rho})$ to $\tilde{O}(n^{1 + \rho})$. We also make it more general, by handling non-binary messages and applying programmable bootstrapping. To obtain a concrete instantiation of our bootstrapping algorithm, we propose a double-CRT (aka RNS) version of the GSW scheme, including a new operation, called shrinking, used to speed-up homomorphic operations by reducing the dimension and ciphertext modulus of the ciphertexts. We also provide a C++ implementation of our algorithm, thus showing for the first time the practicability of the amortized bootstrapping. Moreover, it is competitive with existing bootstrapping algorithms, being even around 3.4 times faster than an equivalent non-amortized version of our bootstrapping

Overflow-detectable Floating-point Fully Homomorphic Encryption

We propose a floating-point fully homomorphic encryption (FPFHE) based on torus fully homomorphic encryption equipped with programmable bootstrapping. Specifically, FPFHE for 32-bit and 64-bit floating-point messages are implemented, the latter being state-of-the-art precision in FHEs. Also, a ciphertext is constructed to check if an overflow had occurred or not while evaluating arithmetic circuits with FPFHE, which is useful when the message space or arithmetic circuit is too complex to estimate a bound of outputs such as deep learning applications