CryptoDB
Dengguo Feng
ORCID: 0000-0002-8515-7124
Publications
Year
Venue
Title
2024
ASIACRYPT
NTRU-based Bootstrapping for MK-FHEs without using Overstretched Parameters
Abstract
Recent attacks on NTRU lattices given by Ducas and van Woerden (ASIACRYPT 2021) showed that for moduli $q$ larger than the so-called fatigue point $n^{2.484+o(1)}$, the security of NTRU is noticeably less than that of (ring)-LWE. Unlike NTRU-based PKE with $q$ typically lying in the secure regime of NTRU lattices (i.e., $q<n^{2.484+o(1)}$), the security of existing NTRU-based multi-key FHEs (MK-FHEs) requiring $q=O(n^k)$ for $k$ keys could be significantly affected by those attacks.
In this paper, we first propose a (matrix) NTRU-based MK-FHE for super-constant number $k$ of keys without using overstretched NTRU parameters. Our scheme is essentially a combination of two components following the two-layer framework of TFHE/FHEW:
- a simple first-layer matrix NTRU-based encryption which naturally supports multi-key NAND operations with moduli $q=O(k\cdot n^{1.5})$ only linear in the number $k$ of keys;
- and a crucial second-layer NTRU-based encryption which supports efficient hybrid product between a single-key ciphertext and a multi-key ciphertext for gate bootstrapping.
Then, by replacing the first-layer with a more efficient LWE-based multi-key encryption,
we obtain an improved MK-FHE scheme with better performance. We also employ a light key-switching technique to reduce the key-switching key size from previous $O(n^2)$ bits to $O(n)$ bits.
A proof-of-concept implementation shows that our two MK-FHE schemes outperform the state-of-the-art TFHE-like MK-FHE schemes in both computation efficiency and bootstrapping key size. Concretely, for $k=8$ at the same 100-bit security level, our improved MK-FHE scheme can bootstrap a ciphertext in {0.54s} on a laptop and only has a bootstrapping key of size {13.89}MB,
which are respectively 2.2 times faster and 7.4 times smaller than the MK-FHE scheme (which relies on a second-layer encryption from the ring-LWE assumption) due to Chen, Chillotti and Song (ASIACRYPT 2019).
2023
CRYPTO
Fast Blind Rotation for Bootstrapping FHEs
Abstract
Blind rotation is one of the key techniques to construct fully homomorphic encryptions with the best known bootstrapping algorithms running in less than one second. Currently, the two main approaches, namely, AP and GINX, for realizing blind rotation are first introduced by Alperin-Sheriff and Peikert (CRYPTO 2014) and Gama, Izabachene, Nguyen and Xie (EUROCRYPT 2016), respectively.
In this paper, we propose a new blind rotation algorithm based on a GSW-like encryption from the NTRU assumption. Our algorithm has performance asymptotically independent from the key distributions, and outperforms AP and GINX in both the evaluation key size and the computational efficiency (especially for large key distributions). By using our blind rotation algorithm as a building block, we present new bootstrapping algorithms for both LWE and RLWE ciphertexts.
We implement our bootstrapping algorithm for LWE ciphertexts, and compare the actual performance with two bootstrapping algorithms, namely, FHEW/AP by Ducas and Micciancio (EUROCRYPT 2015) and TFHE/GINX by Chillotti, Gama, Georgieva and Izabach\`ene (Journal of Cryptology 2020), that were implemented in the OpenFHE library. For parameters with ternary key distribution at 128-bit security, our bootstrapping only needs to store evaluation key of size 18.65MB for blind rotation, which is about 89.8 times smaller than FHEW/AP and 2.9 times smaller than TFHE/GINX. Moreover, our bootstrapping can be done in 112ms on a laptop, which is about 3.2 times faster than FHEW/AP and 2.1 times faster than TFHE/GINX. More improvements are available for large key distributions such as Gaussian distributions.
2023
ASIACRYPT
NEV: Faster and Smaller NTRU Encryption using Vector Decoding
Abstract
In this paper, we present $\nev$ -- a faster and smaller NTRU Encryption using Vector decoding,
which is provably IND-CPA secure in the standard model
under the decisional NTRU and RLWE assumptions over the cyclotomic ring $R_q = \ZZ_q[X]/(X^n+1)$.
Our main technique is a novel and non-trivial way to integrate a previously known plaintext
encoding and decoding mechanism into the provably IND-CPA secure NTRU variant by Stehl\'e and Steinfeld (Eurocrypt 2011). Unlike the original NTRU encryption and its variants which encode the plaintext into the least significant bits of the coefficients of a message polynomial, we encode each plaintext bit into the most significant bits of multiple coefficients of the message polynomial,
so that we can use a vector of noised coefficients to decode each plaintext bit in decryption,
and significantly reduce the size of $q$ with a reasonably negligible decryption failure.
Concretely, we can use $q = 769$ to obtain public keys and ciphertexts of 615 bytes
with decryption failure $\leq 2^{-138}$ at NIST level 1 security, and 1229 bytes with decryption failure $\leq 2^{-152}$ at NIST level 5 security. By applying the Fujisaki-Okamoto transformation in a standard way, we obtain an IND-CCA secure KEM from our basic PKE scheme. Compared to NTRU and Kyber in the NIST Round 3 finalists at the same security levels, our KEM is 33-48\% more compact and 5.03-29.94X faster than NTRU in the round-trip time of ephemeral key exchange, and is 21\% more compact and 1.42-1.74X faster than Kyber.
\qquad We also give an optimized encryption scheme $\nev'$ with better noise tolerance (and slightly better efficiency) based on a variant of the RLWE problem, called Subset-Sum Parity RLWE problem, which we show is polynomially equivalent to the standard decisional RLWE problem (with different parameters), and maybe of independent interest.
2022
TOSC
Vectorial Decoding Algorithm for Fast Correlation Attack and Its Applications to Stream Cipher Grain-128a
Abstract
Fast correlation attack, pioneered by Meier and Staffelbach, is an important cryptanalysis tool for LFSR-based stream cipher, which exploits the correlation between the LFSR state and key stream and targets at recovering the initial state of LFSR via a decoding algorithm. In this paper, we develop a vectorial decoding algorithm for fast correlation attack, which is a natural generalization of the original binary approach. Our approach benefits from the contributions of all correlations in a subspace. We propose two novel criteria to improve the iterative decoding algorithm. We also give some cryptographic properties of the new FCA which allows us to estimate the efficiency and complexity bounds. Furthermore, we apply this technique to the well-analyzed stream cipher Grain-128a. Based on a hypothesis, an interesting result for its security bound is deduced from the perspective of iterative decoding. Our analysis reveals the potential vulnerability for LFSRs over matrix ring and also for nonlinear functions with biased multidimensional linear approximations such as Grain-128a.
2022
TOSC
Practical Attacks on Full-round FRIET
Abstract
FRIET is a duplex-based authenticated encryption scheme proposed at EUROCRYPT 2020. It follows a novel design approach for built-in countermeasures against fault attacks. By a judicious choice of components, the designers propose the permutation FRIET-PC that can be used to build an authenticated encryption cipher denoted as FRIET-AE. And FRIET-AE provides a 128-bit security claim for integrity and confidentiality. In this paper, we research the propagation of pairs of differences and liner masks through the round function of FRIET-PC. For the full-round FRIET-PC, we can construct a differential distinguisher whose probability is 1 and a linear distinguisher whose absolute value of correlation is 1. Moreover, we use the differential distinguisher with probability 1 to construct a set consisting of valid tags and ciphertexts which are not created by legal users. This breaks FRIET-AE’s security claim for integrity and confidentiality. As far as we know, this is the first practical attack that threatens the security of FRIET-AE.
2013
CRYPTO
Coauthors
- Hui Chen (1)
- Yiran Dai (1)
- Yi Deng (3)
- Le Dong (1)
- Xiutao Feng (1)
- Dengguo Feng (13)
- Vipul Goyal (1)
- Jie Guan (1)
- Jian Guo (1)
- Bin Hu (1)
- Xuejia Lai (1)
- Zhenqi Li (1)
- Dongdai Lin (2)
- Jun Liu (1)
- Amit Sahai (1)
- Tairong Shi (1)
- Xiaoyun Wang (1)
- Kaixing Wang (1)
- Senpeng Wang (1)
- Shuang Wu (1)
- Chuankun Wu (1)
- Wenling Wu (1)
- Binwu Xiang (2)
- Chao Xu (2)
- Di Yan (1)
- Xiuyuan Yu (1)
- Moti Yung (1)
- Jiang Zhang (3)
- Bin Zhang (5)
- Zhaocun Zhou (2)
- Jian Zou (1)