A New Difference Method for Side-Channel Analysis with High-Dimensional Leakage Models

Heuser, Annelie; Kasper, Michael; Schindler, Werner; Stöttinger, Marc

doi:10.1007/978-3-642-27954-6_23

Cited by 29 publications

(20 citation statements)

References 15 publications

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“…For the analysis of side channel information, many different distinguishers exist [60,90]. Distinguishers are the statistical methods which are applied to side channel measurements.…”

Section: Side Channel Attacksmentioning

confidence: 99%

“…The Global Success Rate is defined as the probability that the complete key is ranked first, i.e., it is the probability of getting the correct value for all key bytes simultaneously [85]. The Partial Success Rate is defined as the probability that the correct subkey is ranked first among all possible subkeys, i.e., the Partial Success Rate (PSR) is the probability of obtaining the correct value, computed independently for each key byte [90]. Since each key byte has its own PSR, often the minimal PSR (min PSR) is used to describe the attack efficiency [165].…”

Section: Side Channel Attacksmentioning

confidence: 99%

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Why cryptography should not rely on physical attack complexity

Krämer

2016

It - Information Technology

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Ich versichere an Eides statt, dass ich diese Dissertation selbständig verfasst und nur die angegebenen Quellen und Hilfsmittel verwendet habe. Datum Für meine Eltern AbstractEver since the first side channel attacks and fault attacks on cryptographic devices were introduced in the mid-nineties, new possibilities of physical attacks have been consistently explored. The risk that these attacks pose is reduced by reacting to known attacks and by developing and implementing countermeasures against them. For physical attacks whose theory is known but which have not been conducted yet, however, the situation is different. Attacks whose physical realization is assumed to be very complex are taken less seriously. The trust that these attacks will not be realized due to their physical complexity means that no countermeasures are developed at all. This leads to unprotected devices once the assessment of the complexity turns out to be wrong.This thesis presents two practical physical attacks whose theory is known for several years. Since neither attack has previously been successfully implemented in practice, however, they were not considered a serious threat. Their physical attack complexity has been overestimated and the implied security threat has been underestimated. First, we introduce the photonic side channel, which offers not only temporal resolution, but also the highest possible spatial resolution. Due to the high cost of its first realization, it has not been taken seriously. We show both simple and differential photonic side channel analyses. Then, we present a fault attack against pairing-based cryptography. Due to the need for at least two independent precise faults in a single pairing computation, it has also not been taken seriously. We show how attackers can reveal the secret key of symmetric as well as asymmetric cryptographic algorithms based on these physical attacks. We present countermeasures on the software and the hardware level, which help to prevent these attacks in the future.Based on these two presented attacks, this thesis shows that the assessment of physical attack complexity is error-prone. Hence, cryptography should not rely on it. Cryptographic technologies have to be protected against all physical attacks, have they already been realized or not. The development of countermeasures does not require the successful execution of an attack but can already be carried out as soon as the principle of a side channel or a fault attack is understood.

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“…For the analysis of side channel information, many different distinguishers exist [60,90]. Distinguishers are the statistical methods which are applied to side channel measurements.…”

Section: Side Channel Attacksmentioning

confidence: 99%

Section: Side Channel Attacksmentioning

confidence: 99%

Why cryptography should not rely on physical attack complexity

Krämer

2016

It - Information Technology

View full text Add to dashboard Cite

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“…All the sample selection methods from Section 3 can be adapted for stochastic models by using (11) and (14) to compute the stochastic mean vectorsx k and covariance matrixŜ, and then using these to obtain the desired signal-strength estimate s j . In addition, Schindler et al [2] proposed to use s j = u−1 b=1 β 2 jb , i.e.…”

Section: Sample Selectionmentioning

confidence: 99%

“…However, until now, the sole published attempt to apply PCA to stochastic models, by Heuser et al [11], is inefficient. As we have shown earlier, for template attacks, the goal of PCA is to find the eigenvectors u j such that the projection in (16) maximises the distance between the compressed traces corresponding to different values k. Instead of using the eigenvectors of B ("supervised approach"), Heuser et al [11] used those of the raw covariance matrix S r , computed as in (14), to project the leakage traces. While this removes the correlation between leakage samples, it does not maximise the discrimination between means, since the matrixŜ r contains no information about the different raw mean vectorsx r k , obtained from (11), thereby forming an "unsupervised approach".…”

Section: Pca and Ldamentioning

confidence: 99%

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Efficient Stochastic Methods: Profiled Attacks Beyond 8 Bits

Choudary

Kühn

2015

Lecture Notes in Computer Science

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Abstract. Template attacks and stochastic models are among the most powerful side-channel attacks. However, they can be computationally expensive when processing a large number of samples. Various compression techniques have been used very successfully to reduce the data dimensionality prior to applying template attacks, most notably Principal Component Analysis (PCA) and Fisher's Linear Discriminant Analysis (LDA). These make the attacks more efficient computationally and help the profiling phase to converge faster. We show how these ideas can also be applied to implement stochastic models more efficiently, and we also show that they can be applied and evaluated even for more than eight unknown data bits at once.

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It Started with Templates: The Future of Profiling in Side-Channel Analysis

Batina

Djukanović

Heuser

et al. 2021

Security of Ubiquitous Computing Systems

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Side-channel attacks (SCAs) are powerful attacks based on the information obtained from the implementation of cryptographic devices. Profiling side-channel attacks has received a lot of attention in recent years due to the fact that this type of attack defines the worst-case security assumptions. The SCA community realized that the same approach is actually used in other domains in the form of supervised machine learning. Consequently, some researchers started experimenting with different machine learning techniques and evaluating their effectiveness in the SCA context. More recently, we are witnessing an increase in the use of deep learning techniques in the SCA community with strong first results in side-channel analyses, even in the presence of countermeasures. In this chapter, we consider the evolution of profiling attacks, and subsequently we discuss the impacts they have made in the data preprocessing, feature engineering, and classification phases. We also speculate on the future directions and the best-case consequences for the security of small devices.

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A New Difference Method for Side-Channel Analysis with High-Dimensional Leakage Models

Cited by 29 publications

References 15 publications

Why cryptography should not rely on physical attack complexity

Why cryptography should not rely on physical attack complexity

Efficient Stochastic Methods: Profiled Attacks Beyond 8 Bits

It Started with Templates: The Future of Profiling in Side-Channel Analysis

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