You cannot hide behind the mask : power analysis on a provably secure S-box implementation

Power analysis has shown to be successful in breaking symmetric cryptographic algorithms implemented on low resource devices. Prompted by the breaking of many protected implementations in practice, researchers saw the need of validating security of implementations with formal methods. Three generic S-box implementation methods have been proposed by Prouff el al., together with formal proofs of their security against 1st or 2nd-order side-channel analysis. These methods use a similar combination of masking and hiding countermeasures. In this paper, we show that although proven resistant to standard power analysis, these implementation methods are vulnerable to a more sophisticated form of power analysis that combines Differential Power Analysis (DPA) and pattern matching techniques. This new form of power analysis is possible under the same assumptions about power leakage as standard DPA attacks and the added complexity is limited: our experiments show that 900 traces are sufficient to break these algorithms on a device where 150 traces are typically needed for standard DPA. We conclude that the defense strategies—hiding by repeating operations for each possible value, and masking and hiding using the same random number—can create new vulnerabilities

Mexico: Stabilization, Reform, and No Growth

macroeconomics, Mexico, stabilization, reform

Sarcomere Lattice Geometry Influences Cooperative Myosin Binding in Muscle

In muscle, force emerges from myosin binding with actin (forming a cross-bridge). This actomyosin binding depends upon myofilament geometry, kinetics of thin-filament Ca2+ activation, and kinetics of cross-bridge cycling. Binding occurs within a compliant network of protein filaments where there is mechanical coupling between myosins along the thick-filament backbone and between actin monomers along the thin filament. Such mechanical coupling precludes using ordinary differential equation models when examining the effects of lattice geometry, kinetics, or compliance on force production. This study uses two stochastically driven, spatially explicit models to predict levels of cross-bridge binding, force, thin-filament Ca2+ activation, and ATP utilization. One model incorporates the 2-to-1 ratio of thin to thick filaments of vertebrate striated muscle (multi-filament model), while the other comprises only one thick and one thin filament (two-filament model). Simulations comparing these models show that the multi-filament predictions of force, fractional cross-bridge binding, and cross-bridge turnover are more consistent with published experimental values. Furthermore, the values predicted by the multi-filament model are greater than those values predicted by the two-filament model. These increases are larger than the relative increase of potential inter-filament interactions in the multi-filament model versus the two-filament model. This amplification of coordinated cross-bridge binding and cycling indicates a mechanism of cooperativity that depends on sarcomere lattice geometry, specifically the ratio and arrangement of myofilaments

Simultaneous intracranial EEG and fMRI of interictal epileptic discharges in humans

Simultaneous scalp EEG–fMRI measurements allow the study of epileptic networks and more generally, of the coupling between neuronal activity and haemodynamic changes in the brain. Intracranial EEG (icEEG) has greater sensitivity and spatial specificity than scalp EEG but limited spatial sampling. We performed simultaneous icEEG and functional MRI recordings in epileptic patients to study the haemodynamic correlates of intracranial interictal epileptic discharges (IED). Two patients undergoing icEEG with subdural and depth electrodes as part of the presurgical assessment of their pharmaco-resistant epilepsy participated in the study. They were scanned on a 1.5 T MR scanner following a strict safety protocol. Simultaneous recordings of fMRI and icEEG were obtained at rest. IED were subsequently visually identified on icEEG and their fMRI correlates were mapped using a general linear model (GLM). On scalp EEG–fMRI recordings performed prior to the implantation, no IED were detected. icEEG–fMRI was well tolerated and no adverse health effect was observed. intra-MR icEEG was comparable to that obtained outside the scanner. In both cases, significant haemodynamic changes were revealed in relation to IED, both close to the most active electrode contacts and at distant sites. In one case, results showed an epileptic network including regions that could not be sampled by icEEG, in agreement with findings from magneto-encephalography, offering some explanation for the persistence of seizures after surgery. Hence, icEEG–fMRI allows the study of whole-brain human epileptic networks with unprecedented sensitivity and specificity. This could help improve our understanding of epileptic networks with possible implications for epilepsy surgery

Differential Power Analysis of the SKINNY Family of Block Ciphers

The SKINNY family of lightweight block ciphers is well-researched in terms of standard cryptanalysis, but little has been done in the field of power analysis attacks. By sequentially dividing and conquering, univariate Differential Power Analysis attacks are performed against SKINNY. As the resulting diffusion from MixColumns introduces redundancy in terms of leakage, we introduce an alternative placement scheme for the tweak material in the related-tweakey setting to minimize leakage of the key material.Masteroppgave i informatikkINF399MAMN-INFMAMN-PRO

Research On Hardware-based Hiding Countermeasures Against Power Analysis Attacks

電気通信大学202

Improving Non-Profiled Side-Channel Attacks using Autoencoder based Preprocessing

In recent years, deep learning-based side-channel attacks have established their position as mainstream. However, most deep learning techniques for cryptanalysis mainly focused on classifying side-channel information in a profiled scenario where attackers can obtain a label of training data. In this paper, we introduce a novel approach with deep learning for improving side-channel attacks, especially in a non-profiling scenario. We also propose a new principle of training that trains an autoencoder through the noise from real data using noise-reduced labels. It notably diminishes the noise in measurements by modifying the autoencoder framework to the signal preprocessing. We present convincing comparisons on our custom dataset, captured from ChipWhisperer-Lite board, that demonstrate our approach outperforms conventional preprocessing methods such as principal component analysis and linear discriminant analysis. Furthermore, we apply the proposed methodology to realign de-synchronized traces that applied hiding countermeasures, and we experimentally validate the performance of the proposal. Finally, we experimentally show that we can improve the performance of higher-order side-channel attacks by using the proposed technique with domain knowledge for masking countermeasures

Capital Account Liberalisation: Empirical Evidence and Policy Capital Account Liberalisation: Empirical Evidence and Policy Issues - I

This paper documents trends in capital flows into India in a comparative perspective,examines the impact of these flows on key macroeconomic variables and discusses the implications for economic policy........capital flows; capital account liberalisation; exchange rate appreciation; sterilisation;macroeconomic policy