International Association for Cryptologic Research

International Association
for Cryptologic Research

CryptoDB

Naofumi Homma

Publications

Year
Venue
Title
2021
ASIACRYPT
Fault-Injection Attacks against NIST’s Post-Quantum Cryptography Round 3 KEM Candidates
We investigate __all__ NIST PQC Round 3 KEM candidates from the viewpoint of fault-injection attacks: Classic McEliece, Kyber, NTRU, Saber, BIKE, FrodoKEM, HQC, NTRU Prime, and SIKE. All KEM schemes use variants of the Fujisaki-Okamoto transformation, so the equality test with re-encryption in decapsulation is critical. We survey effective key-recovery attacks when we can skip the equality test. We found the existing key-recovery attacks against Kyber, NTRU, Saber, FrodoKEM, HQC, one of two KEM schemes in NTRU Prime, and SIKE. We propose a new key-recovery attack against the other KEM scheme in NTRU Prime. We also report an attack against BIKE that leads to leakage of information of secret keys. The open-source pqm4 library contains all KEM schemes except Classic McEliece and HQC. We show that giving a single instruction-skipping fault in the decapsulation processes leads to skipping the equality test __virtually__ for Kyber, NTRU, Saber, BIKE, and SIKE. We also report the experimental attacks against them. We also report the implementation of NTRU Prime allows chosen-ciphertext attacks freely and the timing side-channel of FrodoKEM reported in Guo, Johansson, and Nilsson (CRYPTO 2020) remains, while there are no such bugs in their NIST PQC Round 3 submissions.
2020
TCHES
Rejection Sampling Schemes for Extracting Uniform Distribution from Biased PUFs 📺
Rei Ueno Kohei Kazumori Naofumi Homma
This paper presents an efficient fuzzy extractor (FE) construction for secure cryptographic key generation from physically unclonable functions (PUFs). The proposed FE, named acceptance-or-rejection (AR)-based FE, utilizes a new debiasing scheme to extract a uniform distribution from a biased PUF response. The proposed debiasing scheme employs the principle of rejection sampling, and can extract a longer debiased bit string compared to those of conventional debiasing schemes. In addition, the proposed AR-based FE is extended to ternary PUF responses (i.e., ternary encoding of a PUF response). These responses can be derived according to cell-wise reliability of the PUF and are promising for extraction of stable and high-entropy responses from common PUFs. The performance of the AR-based Fes is evaluated through an experimental simulation of PUF-based key generation and compared with conventional FEs. We confirm that the proposed AR-based FE can achieve the highest efficiency in terms of PUF and nonvolatile memory (NVM) sizes for various PUF conditions among the conventional counterparts. More precisely, the AR-based FE can realize a 128-bit key generation with up-to 55% smaller PUF size or up-to 72% smaller NVM size than other conventional FEs. In addition, the ternary AR-based FE is up to 55% more efficient than the binary version, and can also achieve up-to 63% higher efficiency than conventional counterparts. Furthermore, we show that the AR-based FE can be applied to PUFs with local biases (e.g., biases depending on cell location in SRAM PUFs), unlike all the conventional schemes, for which only global (or identical) biases are assumed.
2017
JOFC
2016
CHES
2015
EPRINT
2015
CHES
2014
EPRINT
2014
CHES
2008
CHES
2008
CHES
2006
CHES

Program Committees

CHES 2019
CHES 2018
CHES 2017 (Program chair)
CHES 2016
CHES 2015
CHES 2012
CHES 2011
CHES 2009