## CryptoDB

### Ilaria Chillotti

#### Publications

Year
Venue
Title
2021
ASIACRYPT
Fully Homomorphic Encryption} (FHE) schemes enable to compute over encrypted data. Among them, TFHE [CGGI17] has the great advantage of offering an efficient method for bootstrapping noisy ciphertexts, i.e., reduce the noise. Indeed, homomorphic computation increases the noise in ciphertexts and might compromise the encrypted message. TFHE bootstrapping, in addition to reducing the noise, also evaluates (for free) univariate functions expressed as look-up tables. It however requires to have the most significant bit of the plaintext to be known a priori, resulting in the loss of one bit of space to store messages. Furthermore it represents a non negligible overhead in terms of computation in many use cases. In this paper, we propose a solution to overcome this limitation, that we call Programmable Bootstrapping Without Padding (WoP-PBS). This approach relies on two building blocks. The first one is the multiplication à la BFV [FV12] that we incorporate into TFHE. This is possible thanks to a thorough noise analysis showing that correct multiplications can be computed using practical TFHE parameters. The second building block is the generalization of TFHE bootstrapping introduced in this paper. It offers the flexibility to select any chunk of bits in an encrypted plaintext during a bootstrap. It also enables to evaluate many LUTs at the same time when working with small enough precision. All these improvements are particularly helpful in some applications such as the evaluation of Boolean circuits (where a bootstrap is no longer required in each evaluated gate) and, more generally, in the efficient evaluation of arithmetic circuits even with large integers. Those results improve TFHE circuit bootstrapping as well. Moreover, we show that bootstrapping large precision integers is now possible using much smaller parameters than those obtained by scaling TFHE ones.
2019
EUROCRYPT
Since Cheon et al. introduced a homomorphic encryption scheme for approximate arithmetic (Asiacrypt ’17), it has been recognized as suitable for important real-life usecases of homomorphic encryption, including training of machine learning models over encrypted data. A follow up work by Cheon et al. (Eurocrypt ’18) described an approximate bootstrapping procedure for the scheme. In this work, we improve upon the previous bootstrapping result. We improve the amortized bootstrapping time per plaintext slot by two orders of magnitude, from $\sim$∼1 s to $\sim$∼0.01 s. To achieve this result, we adopt a smart level-collapsing technique for evaluating DFT-like linear transforms on a ciphertext. Also, we replace the Taylor approximation of the sine function with a more accurate and numerically stable Chebyshev approximation, and design a modified version of the Paterson-Stockmeyer algorithm for fast evaluation of Chebyshev polynomials over encrypted data.
2019
JOFC
This work describes a fast fully homomorphic encryption scheme over the torus (TFHE) that revisits, generalizes and improves the fully homomorphic encryption (FHE) based on GSW and its ring variants. The simplest FHE schemes consist in bootstrapped binary gates. In this gate bootstrapping mode, we show that the scheme FHEW of Ducas and Micciancio (Eurocrypt, 2015) can be expressed only in terms of external product between a GSW and an LWE ciphertext. As a consequence of this result and of other optimizations, we decrease the running time of their bootstrapping from 690 to 13 ms single core, using 16 MB bootstrapping key instead of 1 GB, and preserving the security parameter. In leveled homomorphic mode, we propose two methods to manipulate packed data, in order to decrease the ciphertext expansion and to optimize the evaluation of lookup tables and arbitrary functions in ${\mathrm {RingGSW}}$RingGSW-based homomorphic schemes. We also extend the automata logic, introduced in Gama et al. (Eurocrypt, 2016), to the efficient leveled evaluation of weighted automata, and present a new homomorphic counter called $\mathrm {TBSR}$TBSR, that supports all the elementary operations that occur in a multiplication. These improvements speed up the evaluation of most arithmetic functions in a packed leveled mode, with a noise overhead that remains additive. We finally present a new circuit bootstrapping that converts $\mathsf {LWE}$LWE ciphertexts into low-noise ${\mathrm {RingGSW}}$RingGSW ciphertexts in just 137 ms, which makes the leveled mode of TFHE composable and which is fast enough to speed up arithmetic functions, compared to the gate bootstrapping approach. Finally, we provide an alternative practical analysis of LWE based schemes, which directly relates the security parameter to the error rate of LWE and the entropy of the LWE secret key, and we propose concrete parameter sets and timing comparison for all our constructions.
2019
ASIACRYPT
In this paper, we propose a Multi-Key Homomorphic Encryption (MKHE) scheme by generalizing the low-latency homomorphic encryption by Chillotti et al. (ASIACRYPT 2016). Our scheme can evaluate a binary gate on ciphertexts encrypted under different keys followed by a bootstrapping.The biggest challenge to meeting the goal is to design a multiplication between a bootstrapping key of a single party and a multi-key RLWE ciphertext. We propose two different algorithms for this hybrid product. Our first method improves the ciphertext extension by Mukherjee and Wichs (EUROCRYPT 2016) to provide better performance. The other one is a whole new approach which has advantages in storage, complexity, and noise growth.Compared to previous work, our construction is more efficient in terms of both asymptotic and concrete complexity. The length of ciphertexts and the computational costs of a binary gate grow linearly and quadratically on the number of parties, respectively. We provide experimental results demonstrating the running time of a homomorphic NAND gate with bootstrapping. To the best of our knowledge, this is the first attempt in the literature to implement an MKHE scheme.
2017
ASIACRYPT
2016
ASIACRYPT

PKC 2022
Crypto 2020

#### Coauthors

Hao Chen (2)
Nicolas Gama (3)
Mariya Georgieva (3)
Malika Izabachène (3)
Damien Ligier (1)
Jean-Baptiste Orfila (1)
Yongsoo Song (2)
Samuel Tap (1)