Affine Masking against Higher-Order Side Channel Analysis

In the last decade, an effort has been made by the research community to find efficient ways to thwart side channel analysis (SCA) against physical implementations of cryptographic algorithms. A common countermeasure for implementations of block ciphers is Boolean masking which randomizes by the bitwise addition of one or several random value(s) to the variables to be protected. However, advanced techniques called higher-order SCA attacks exist that overcome such a countermeasure. These attacks are greatly favored by the very nature of Boolean masking. In this paper, we revisit the affine masking initially introduced by Von Willich in 2001 as an alternative to Boolean masking. We show how to apply it to AES at the cost of a small timing overhead compared to Boolean masking. We then conduct an in-depth analysis pinpointing the leakage reduction implied by affine masking. Our results clearly show that the proposed scheme provides an excellent performance-security trade-off to protect AES against higher-order SCA

Investigating Efficient Deep Learning Architectures For Side-Channel Attacks on AES

Over the past few years, deep learning has been getting progressively more popular for the exploitation of side-channel vulnerabilities in embedded cryptographic applications, as it offers advantages in terms of the amount of attack traces required for effective key recovery. A number of effective attacks using neural networks have already been published, but reducing their cost in terms of the amount of computing resources and data required is an ever-present goal, which we pursue in this work. We focus on the ANSSI Side-Channel Attack Database (ASCAD), and produce a JAX-based framework for deep-learning-based SCA, with which we reproduce a selection of previous results and build upon them in an attempt to improve their performance. We also investigate the effectiveness of various Transformer-based models.Comment: 12 pages, 6 figures. This manuscript is a report produced as part of a T\'el\'ecom Paris "PRIM" (Project Recherche et Innovation Master / Master's Research and Innovation Project

Not so Difficult in the End: Breaking the ASCADv2 Dataset

The ASCADv2 dataset ranks among the most secure publicly available datasets today. Two layers of countermeasures protect it: affine masking and shuffling, and the current attack approaches rely on strong assumptions. Specifically, besides having access to the source code, an adversary also requires prior knowledge of random shares. This paper forgoes reliance on such knowledge and proposes two attack approaches based on the vulnerabilities of the affine mask implementation. As a result, the first attack can retrieve all secret keys\u27 reliance in less than a minute. Although the second attack is not entirely successful in recovering all keys, we believe more traces would help make such an attack fully functional

A Comparison of Multi-task learning and Single-task learning Approaches

In this paper, we provide experimental evidence for the benefits of multi-task learning in the context of masked AES implementations (via the ASCADv1-r and ASCADv2 databases). We develop an approach for comparing single-task and multi-task approaches rather than comparing specific resulting models: we do this by training many models with random hyperparameters (instead of comparing a few highly tuned models). We find that multi-task learning has significant practical advantages that make it an attractive option in the context of device evaluations: the multi-task approach leads to performant networks quickly in particular in situations where knowledge of internal randomness is not available during training

Side-Channel Countermeasures\u27 Dissection and the Limits of Closed Source Security Evaluations

We take advantage of a recently published open source implementation of the AES protected with a mix of countermeasures against side-channel attacks to discuss both the challenges in protecting COTS devices against such attacks and the limitations of closed source security evaluations. The target implementation has been proposed by the French ANSSI (Agence Nationale de la Sécurité des Systèmes d\u27Information) to stimulate research on the design and evaluation of side-channel secure implementations. It combines additive and multiplicative secret sharings into an affine masking scheme that is additionally mixed with a shuffled execution. Its preliminary leakage assessment did not detect data dependencies with up to 100,000 measurements. We first exhibit the gap between such a preliminary leakage assessment and advanced attacks by exhibiting how a countermeasures\u27 dissection exploiting a mix of dimensionality reduction, multivariate information extraction and key enumeration can recover the full key with less than 2,000 measurements. We then discuss the relevance of open source evaluations to analyze such implementations efficiently, by exhibiting that certain steps of the attack are hard to automate without implementation knowledge (even with machine learning tools), while performing them manually is trivial. Our findings are not due to design flaws but from the general difficulty to prevent side-channel attacks in COTS devices with limited noise. We anticipate that high security on such devices requires significantly more shares

Making Masking Security Proofs Concrete - Or How to Evaluate the Security of any Leaking Device

We investigate the relationships between theoretical studies of leaking cryptographic devices and concrete security evaluations with standard side-channel attacks. Our contributions are in four parts. First, we connect the formal analysis of the masking countermeasure proposed by Duc et al. (Eurocrypt 2014) with the Eurocrypt 2009 evaluation framework for side-channel key recovery attacks. In particular, we re-state their main proof for the masking countermeasure based on a mutual information metric, which is frequently used in concrete physical security evaluations. Second, we discuss the tightness of the Eurocrypt 2014 bounds based on experimental case studies. This allows us to conjecture a simplified link between the mutual information metric and the success rate of a side-channel adversary, ignoring technical parameters and proof artifacts. Third, we introduce heuristic (yet well-motivated) tools for the evaluation of the masking countermeasure when its independent leakage assumption is not perfectly fulfilled, as it is frequently encountered in practice. Thanks to these tools, we argue that masking with non-independent leakages may provide improved security levels in certain scenarios. Eventually, we consider the tradeoff between measurement complexity and key enumeration in divide-and-conquer side-channel attacks, and show that it can be predicted based on the mutual information metric, by solving a non-linear integer programming problem for which efficient solutions exist. The combination of these observations enables significant reductions of the evaluation costs for certification bodies

Effective and Efficient Masking with Low Noise using Small-Mersenne-Prime Ciphers

Embedded devices used in security applications are natural targets for physical attacks. Thus, enhancing their side-channel resistance is an important research challenge. A standard solution for this purpose is the use of Boolean masking schemes, as they are well adapted to current block ciphers with efficient bitslice representations. Boolean masking guarantees that the security of an implementation grows exponentially in the number of shares under the assumption that leakages are sufficiently noisy (and independent). Unfortunately, it has been shown that this noise assumption is hardly met on low-end devices. In this paper, we therefore investigate techniques to mask cryptographic algorithms in such a way that their resistance can survive an almost complete lack of noise. Building on seed theoretical results of Dziembowski et al., we put forward that arithmetic encodings in prime fields can reach this goal. We first exhibit the gains that such encodings lead to thanks to a simulated information theoretic analysis of their leakage (with up to six shares). We then provide figures showing that on platforms where optimized arithmetic adders and multipliers are readily available (i.e., most MCUs and FPGAs), performing masked operations in small to medium Mersenne-prime fields as opposed to binary extension fields will not lead to notable implementation overheads. We compile these observations into a new AES-like block cipher, called AES-prime, which is well-suited to illustrate the remarkable advantages of masking in prime fields. We also confirm the practical relevance of our findings by evaluating concrete software (ARM Cortex-M3) and hardware (Xilinx Spartan-6) implementations. Our experimental results show that security gains over Boolean masking (and, more generally, binary encodings) can reach orders of magnitude despite the same amount of information being leaked per share

Effective and Efficient Masking with Low Noise Using Small-Mersenne-Prime Ciphers

Embedded devices used in security applications are natural targets for physical attacks. Thus, enhancing their side-channel resistance is an important research challenge. A standard solution for this purpose is the use of Boolean masking schemes, as they are well adapted to current block ciphers with efficient bitslice representations. Boolean masking guarantees that the security of an implementation grows exponentially in the number of shares under the assumption that leakages are sufficiently noisy (and independent). Unfortunately, it has been shown that this noise assumption is hardly met on low-end devices. In this paper, we therefore investigate techniques to mask cryptographic algorithms in such a way that their resistance can survive an almost complete lack of noise. Building on seed theoretical results of Dziembowski et al., we put forward that arithmetic encodings in prime fields can reach this goal. We first exhibit the gains that such encodings lead to thanks to a simulated information theoretic analysis of their leakage (with up to six shares). We then provide figures showing that on platforms where optimized arithmetic adders and multipliers are readily available (i.e., most MCUs and FPGAs), performing masked operations in small to medium Mersenne-prime fields as opposed to binary extension fields will not lead to notable implementation overheads. We compile these observations into a new AES-like block cipher, called AES-prime, which is well-suited to illustrate the remarkable advantages of masking in prime fields. We also confirm the practical relevance of our findings by evaluating concrete software (ARM Cortex-M3) and hardware (Xilinx Spartan-6) implementations. Our experimental results show that security gains over Boolean masking (and, more generally, binary encodings) can reach orders of magnitude despite the same amount of information being leaked per share