International Association
for Cryptologic Research

<p>This paper presents a new side-channel attack (SCA) on unrolled implementations of stream ciphers, with a particular focus on Trivium. Most conventional SCAs predominantly concentrate on leakage of some first rounds prior to the sufficient diffusion of the secret key and initial vector (IV). However, recently, unrolled hardware implementation has become common and practical, which achieves higher throughput and energy efficiency compared to a round-based hardware. The applicability of conventional SCAs to such unrolled hardware is unclear because the leakage of the first rounds from unrolled hardware is hardly observed. In this paper, focusing on Trivium, we propose a novel SCA on unrolled stream cipher hardware, which can exploit leakage of rounds latter than 80, while existing SCAs exploited intermediate values earlier than 80 rounds. We first analyze the algebraic equations representing the intermediate values of these rounds and present the recursive restricted linear decomposition (RRLD) strategy. This approach uses correlation power analysis (CPA) to estimate the intermediate values of latter rounds. Furthermore, we present a chosen-IV strategy for a successful key recovery through linearization. We experimentally demonstrate that the proposed SCA achieves the key recovery of a 288-round unrolled Trivium hardware implementation using 360,000 traces. Finally, we evaluate the performance of unrolled Trivium hardware implementations to clarify the trade-off between performance and SCA (in)security. The proposed SCA requires 34.5 M traces for a key recovery of 384-round unrolled Trivium implementation and is not applicable to 576-round unrolled hardware. </p>

This paper presents the first security evaluation of exponent-blinded RSA–CRT implementation with sliding window exponentiation against cache attacks. Our main contributions are threefold. (1) We demonstrate an improved cache attack using Flush+Reload on RSA–CRT to estimate the squaring–multiplication operational sequence. The proposed method can estimate a correct squaring–multiplication sequence from one Flush+Reload trace, while the existing Flush+Reload attacks always contain errors in the sequence estimation. This is mandatory for the subsequent steps in the proposed attack. (2) We present a new and first partial key exposure attack on exponent-blinded RSA–CRT with a random-bit leak. The proposed attack first estimates a random mask for blinding exponent using a modification of the Schindler–Wiemers continued fraction attack, and then recovers the secret key using an extension of the Heninger–Shacham branch-and-prune attack. We experimentally show that the proposed attack on RSA–CRT using a practical window size of 5 with 16-, 32-, and 64-bit masks is carried out with complexity of 225.6, 267.7, and 2161, respectively. (3) We then investigate the tradeoffs between mask bit length and implementation performance. The computational cost of exponent-blinded RSA–CRT using a sliding window with a 32- and 64-bit mask are 15% and 10% faster than that with a 128-bit mask, respectively, as we confirmed that 32- and 64-bit masks are sufficient to defeat the proposed attack. Our source code used in the experiment is publicly available.

In this paper, we present a side-channel analysis (SCA) on key encapsulation mechanisms (KEMs) based on the Fujisaki–Okamoto (FO) transformation and its variants. Many post-quantum KEMs usually perform re-encryption during key decapsulation to achieve chosen-ciphertext attack (CCA) security. The side-channel leakage of re-encryption can be exploited to mount a key-recovery plaintext-checking attack (KR-PCA), even if the chosen-plaintext attack (CCA) secure decryption constructing the KEM is securely implemented. Herein, we propose an efficient side-channel-assisted KR-PCA on post-quantum KEMs, and achieve a key recovery with significantly fewer attack traces than existing ones in TCHES 2022 and 2023. The basic concept of the proposed attack is to introduce a new KR-PCA based on a multiple-valued (MV-)PC oracle and then implement a dedicated MV-PC oracle based on a multi-classification neural network (NN). The proposed attack is applicable to the NIST PQC selected algorithm Kyber and the similar lattice-based Saber, FrodoKEM and NTRU Prime, as well as SIKE. We also present how to realize a sufficiently reliable MV-PC oracle from NN model outputs that are not 100% accurate, and analyze the tradeoff between the key recovery success rate and the number of attack traces. We assess the feasibility of the proposed attack through attack experiments on three typical symmetric primitives to instantiate a random oracle (SHAKE, SHA3, and AES software). The proposed attack reduces the number of attack traces required for a reliable key recovery by up to 87% compared to the existing attacks against Kyber and other lattice-based KEMs, under the condition of 99.9999% success rate for key recovery. The proposed attack can also reduce the number of attack traces by 85% for SIKE.

This paper presents a provably secure, higher-order, and leakage-resilient (LR) rekeying scheme named LR Rekeying with Random oracle Repetition (LR4), along with a quantitative security evaluation methodology. Many existing LR primitives are based on a concept of leveled implementation, which still essentially require a leak-free sanctuary (i.e., differential power analysis (DPA)-resistant component(s)) for some parts. In addition, although several LR pseudorandom functions (PRFs) based on only bounded DPA-resistant components have been developed, their validity and effectiveness for rekeying usage still need to be determined. In contrast, LR4 is formally proven under a leakage model that captures the practical goal of side-channel attack (SCA) protection (e.g., masking with a practical order) and assumes no unbounded DPA-resistant sanctuary. This proof suggests that LR4 resists exponential invocations (up to the birthday bound of key size) without using any unbounded leak-free component, which is the first of its kind. Moreover, we present a quantitative SCA success rate evaluation methodology for LR4 that combines the bounded leakage models for LR cryptography and a state-of-the-art information-theoretical SCA evaluation method. We validate its soundness and effectiveness as a DPA countermeasure through a numerical evaluation; that is, the number of secure calls of a symmetric primitive increases exponentially by increasing a security parameter under practical conditions.

RISC-V is equipped with physical memory protection (PMP) to prevent malicious software from accessing protected memory regions. PMP provides a trusted execution environment (TEE) that isolates secure and insecure applications. In this study, we propose a side-channel-assisted fault-injection attack to bypass isolation based on PMP. The proposed attack scheme involves extracting successful glitch parameters for fault injection from side-channel information under crossdevice conditions. A proof-of-concept TEE compatible with PMP in RISC-V was implemented, and the feasibility and effectiveness of the proposed attack scheme was validated through experiments in TEEs. The results indicate that an attacker can bypass the isolation of the TEE and read data from the protected memory region In addition, we experimentally demonstrate that the proposed attack applies to a real-world TEE, Keystone. Furthermore, we propose a software-based countermeasure that prevents the proposed attack.

This paper presents a side-channel analysis (SCA) on key encapsulation mechanism (KEM) based on the Fujisaki–Okamoto (FO) transformation and its variants. The FO transformation has been widely used in actively securing KEMs from passively secure public key encryption (PKE), as it is employed in most of NIST post-quantum cryptography (PQC) candidates for KEM. The proposed attack exploits side-channel leakage during execution of a pseudorandom function (PRF) or pseudorandom number generator (PRG) in the re-encryption of KEM decapsulation as a plaintext-checking oracle that tells whether the PKE decryption result is equivalent to the reference plaintext. The generality and practicality of the plaintext-checking oracle allow the proposed attack to attain a full-key recovery of various KEMs when an active attack on the underlying PKE is known. This paper demonstrates that the proposed attack can be applied to most NIST PQC third-round KEM candidates, namely, Kyber, Saber, FrodoKEM, NTRU, NTRU Prime, HQC, BIKE, and SIKE (for BIKE, the proposed attack achieves a partial key recovery). The applicability to Classic McEliece is unclear because there is no known active attack on this cryptosystem. This paper also presents a side-channel distinguisher design based on deep learning (DL) for mounting the proposed attack on practical implementation without the use of a profiling device. The feasibility of the proposed attack is evaluated through experimental attacks on various PRF implementations (a SHAKE software, an AES software, an AES hardware, a bit-sliced masked AES software, and a masked AES hardware based on threshold implementation). Although it is difficult to implement the oracle using the leakage from the TI-based masked hardware, the success of the proposed attack against these implementations (even except for the masked hardware), which include masked software, confirms its practicality.

In this study, we present new analytical metrics for evaluating the performance of side-channel attacks (SCAs) by revisiting the perceived information (PI), which is defined using cross-entropy (CE). PI represents the amount of information utilized by a probability distribution that determines a distinguishing rule in SCA. Our analysis partially solves an important open problem in the performance evaluation of deep-learning based SCAs (DL-SCAs) that the relationship between neural network (NN) model evaluation metrics (such as accuracy, loss, and recall) and guessing entropy (GE)/success rate (SR) is unclear. We first theoretically show that the conventional CE/PI is non-calibrated and insufficient for evaluating the SCA performance, as it contains uncertainty in terms of SR. More precisely, we show that an infinite number of probability distributions with different CE/PI can achieve an identical SR. With the above analysis result, we present a modification of CE/PI, named effective CE/PI (ECE/EPI), to eliminate the above uncertainty. The ECE/EPI can be easily calculated for a given probability distribution and dataset, which would be suitable for DL-SCA. Using the ECE/EPI, we can accurately evaluate the SR hrough the validation loss in the training phase, and can measure the generalization of the NN model in terms of SR in the attack phase. We then analyze and discuss the proposed metrics regarding their relationship to SR, conditions of successful attacks for a distinguishing rule with a probability distribution, a statistic/asymptotic aspect, and the order of key ranks in SCA. Finally, we validate the proposed metrics through experimental attacks on masked AES implementations using DL-SCA.

In this paper, a deep-learning based power/EM analysis attack on the state-of-the-art RSA–CRT software implementation is proposed. Our method is applied to a side-channel-aware implementation with the Gnu Multi-Precision (MP) Library, which is a typical open-source software library. Gnu MP employs a fixed-window exponentiation, which is the fastest in a constant time, and loads the entire precomputation table once to avoid side-channel leaks from multiplicands. To conduct an accurate estimation of secret exponents, our method focuses on the process of loading the entire precomputation table, which we call a dummy load scheme. It is particularly noteworthy that the dummy load scheme is implemented as a countermeasure against a simple power/EM analysis (SPA/SEMA). This type of vulnerability from a dummy load scheme also exists in other cryptographic libraries. We also propose a partial key exposure attack suitable for the distribution of errors inthe secret exponents recovered from the windowed exponentiation. We experimentally show that the proposed method consisting of the above power/EM analysis attack, as well as a partial key exposure attack, can be used to fully recover the secret key of the RSA–CRT from the side-channel information of a single decryption or a signature process.

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.

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.