Profiling Good Leakage Models For Masked Implementations

Leakage model plays a very important role in side channel attacks. An accurate leakage model greatly improves the efficiency of attacks. However, how to profile a good enough leakage model, or how to measure the accuracy of a leakage model, is seldom studied. Durvaux et al. proposed leakage certification tests to profile good enough leakage model for unmasked implementations. However, they left the leakage model profiling for protected implementations as an open problem. To solve this problem, we propose the first practical higher-order leakage model certification tests for masked implementations. First and second order attacks are performed on the simulations of serial and parallel implementations of a first-order fixed masking. A third-order attack is performed on another simulation of a second-order random masked implementation. The experimental results show that our new tests can profile the leakage models accurately

Constant-time discrete Gaussian sampling

© 2018 IEEE. Sampling from a discrete Gaussian distribution is an indispensable part of lattice-based cryptography. Several recent works have shown that the timing leakage from a non-constant-time implementation of the discrete Gaussian sampling algorithm could be exploited to recover the secret. In this paper, we propose a constant-time implementation of the Knuth-Yao random walk algorithm for performing constant-time discrete Gaussian sampling. Since the random walk is dictated by a set of input random bits, we can express the generated sample as a function of the input random bits. Hence, our constant-time implementation expresses the unique mapping of the input random-bits to the output sample-bits as a Boolean expression of the random-bits. We use bit-slicing to generate multiple samples in batches and thus increase the throughput of our constant-time sampling manifold. Our experiments on an Intel i7-Broadwell processor show that our method can be as much as 2.4 times faster than the constant-time implementation of cumulative distribution table based sampling and consumes exponentially less memory than the Knuth-Yao algorithm with shuffling for a similar level of security

SNR-Centric Power Trace Extractors for Side-Channel Attacks

The existing power trace extractors consider the case that the number of power traces owned by the attacker is sufficient to guarantee his successful attacks, and the goal of power trace extraction is to lower the complexity rather than increase the success rates. Although having strict theoretical proofs, they are too simple and leakage characteristics of POIs have not been thoroughly analyzed. They only maximize the variance of data-dependent power consumption component and ignore the noise component, which results in very limited SNR to improve and seriously affects the performance of extractors. In this paper, we provide a rigorous theoretical analysis of SNR of power traces, and propose a novel SNR-centric extractor, named Shortest Distance First (SDF), to extract power traces with smallest the estimated noise by taking advantage of known plaintexts. In addition, to maximize the variance of the exploitable component while minimizing the noise, we refer to the SNR estimation model and propose another novel extractor named Maximizing Estimated SNR First (MESF). Finally, we further propose an advanced extractor called Mean optimized MESF (MMESF) that exploits the mean power consumption of each plaintext byte value to more accurately and reasonably estimate the data-dependent power consumption of the corresponding samples. Experiments on both simulated power traces and measurements from an ATmega328p micro-controller demonstrate the superiority of our new extractors

An End-to-end Plaintext-based Side-channel Collision Attack without Trace Segmentation

Side-channel Collision Attacks (SCCA) constitute a subset of non-profiling attacks that exploit information dependency leaked during cryptographic operations. Unlike traditional collision attacks, which seek instances where two different inputs to a cryptographic algorithm yield identical outputs, SCCAs specifically target the internal state, where identical outputs are more likely. In CHES 2023, Staib et al. presented a Deep Learning-based SCCA (DL-SCCA), which enhanced the attack performance while decreasing the required effort for leakage preprocessing. Nevertheless, this method inherits the conventional SCCA\u27s limitations, as it operates on trace segments reflecting the target operation explicitly, leading to issues such as portability and low tolerance to errors. This paper introduces an end-to-end plaintext-based SCCA to address these challenges. We leverage the bijective relationship between plaintext and secret data to label the leakage measurement with known information, then learn plaintext-based profiling models to depict leakages from varying operations. By comparing the leakage representations produced by the profiling model, an adversary can reveal the key difference. As an end-to-end approach, we propose an error correction scheme to rectify false predictions. Experimental results indicate our approach significantly surpasses DL-SCCA in terms of attack performance (e.g., success rate increased from 53\% to 100\%) and computational complexity (training time reduced from approximately 2 hours to 10 minutes). These findings underscore our method\u27s effectiveness and practicality in real-world attack scenarios

OleF: an Inverse-Free Online Cipher. An Online SPRP with an Optimal Inverse-Free Construction

Online ciphers, in spite of being insecure against an sprp adversary, can be desirable at places because of their ease of implementation and speed. Here we propose a single-keyed inverse-free construction that achieves online sprp security with an optimal number of blockcipher calls. We also include a partial block construction, without requiring any extra key

The Superlinearity Problem in Post-Quantum Blockchains

The proof of work mechanism by which many blockchain-based protocols achieve consensus may be undermined by the use of quantum computing in mining—even when all cryptographic primitives are replaced with post-quantum secure alternatives. First, we offer an impossibility result: we prove that quantum (Grover) speedups in solving a large, natural class of proof-of-work puzzles cause an inevitable incentive incompatibility in mining, by distorting the reward structure of mining in proof-of-work-based protocols such as Bitcoin. We refer to such distortion as the Superlinearity Problem. Our impossibility result suggests that for robust post-quantum proof-of-work-based consensus, we may need to look beyond standard cryptographic models. We thus propose a proof-of-work design in a random-beacon model, which is tailored to bypass the earlier impossibility. We conclude with a discussion of open problems, and of the challenges of integrating our new proof-of-work scheme into decentralised consensus protocols under realistic conditions

Standard Lattice-Based Key Encapsulation on Embedded Devices

Lattice-based cryptography is one of the most promising candidates being considered to replace current public-key systems in the era of quantum computing. In 2016, Bos et al. proposed the key exchange scheme FrodoCCS, that is also a submission to the NIST post-quantum standardization process, modified as a key encapsulation mechanism (FrodoKEM). The security of the scheme is based on standard lattices and the learning with errors problem. Due to the large parameters, standard latticebased schemes have long been considered impractical on embedded devices. The FrodoKEM proposal actually comes with parameters that bring standard lattice-based cryptography within reach of being feasible on constrained devices. In this work, we take the final step of efficiently implementing the scheme on a low-cost FPGA and microcontroller devices and thus making conservative post-quantum cryptography practical on small devices. Our FPGA implementation of the decapsulation (the computationally most expensive operation) needs 7,220 look-up tables (LUTs), 3,549 flip-flops (FFs), a single DSP, and only 16 block RAM modules. The maximum clock frequency is 162 MHz and it takes 20.7 ms for the execution of the decapsulation. Our microcontroller implementation has a 66% reduced peak stack usage in comparison to the reference implementation and needs 266 ms for key pair generation, 284 ms for encapsulation, and 286 ms for decapsulation. Our results contribute to the practical evaluation of a post-quantum standardization candidate

An Improved BKW Algorithm for LWE with Applications to Cryptography and Lattices

In this paper, we study the Learning With Errors problem and its binary variant, where secrets and errors are binary or taken in a small interval. We introduce a new variant of the Blum, Kalai and Wasserman algorithm, relying on a quantization step that generalizes and fine-tunes modulus switching. In general this new technique yields a significant gain in the constant in front of the exponent in the overall complexity. We illustrate this by solving p within half a day a LWE instance with dimension n = 128, modulus $q = n^2$, Gaussian noise $\alpha = 1/(\sqrt{n/\pi} \log^2 n)$ and binary secret, using $2^{28}$ samples, while the previous best result based on BKW claims a time complexity of $2^{74}$ with $2^{60}$ samples for the same parameters. We then introduce variants of BDD, GapSVP and UniqueSVP, where the target point is required to lie in the fundamental parallelepiped, and show how the previous algorithm is able to solve these variants in subexponential time. Moreover, we also show how the previous algorithm can be used to solve the BinaryLWE problem with n samples in subexponential time $2^{(\ln 2/2+o(1))n/\log \log n}$. This analysis does not require any heuristic assumption, contrary to other algebraic approaches; instead, it uses a variant of an idea by Lyubashevsky to generate many samples from a small number of samples. This makes it possible to asymptotically and heuristically break the NTRU cryptosystem in subexponential time (without contradicting its security assumption). We are also able to solve subset sum problems in subexponential time for density $o(1)$, which is of independent interest: for such density, the previous best algorithm requires exponential time. As a direct application, we can solve in subexponential time the parameters of a cryptosystem based on this problem proposed at TCC 2010.Comment: CRYPTO 201