White-Box AES Implementation Revisited

White-box cryptography is an obfuscation technique for protecting secret keys in software implementations even if an adversary has full access to the implementation of the encryption algorithm and full control over its execution platforms. This concept was presented by Chow et al. with white-box implementations of DES and AES in 2002. The strategy used in the implementations has become a design principle for subsequent white-box implementations. However, despite its practical importance, progress has not been substantial. In fact, it is repeated that as a proposal for a white-box implementation is reported, an attack of lower complexity is soon announced. This is mainly because most cryptanalytic methods target specific implementations, and there is no general attack tool for white-box cryptography. In this paper, we present an analytic toolbox on white-box implementations in this design framework and show how to reveal the secret information obfuscated in the implementation using this. For a substitution-linear transformation cipher on $n$ bits with S-boxes on $m$ bits, if $m_Q$-bit nonlinear encodings are used to obfuscate output values in the implementation, our attack tool can remove the nonlinear encodings with complexity $O(\frac{n}{m_Q}2^{3m_Q})$. We should increase $m_Q$ to obtain higher security, but it yields exponential storage blowing up and so there are limits to increase the security using the nonlinear encoding. If the inverse of the encoded round function $F$ on $n$ bits is given, the affine encoding $A$ can be recovered in $O(\frac{n}{m}\cdot{m_A}^32^{3m})$ time using our specialized affine equivalence algorithm, where $m_A$ is the smallest integer $p$ such that $A$ (or its similar matrix obtained by permuting rows and columns) is a block-diagonal matrix with $p\times p$ matrix blocks. According to our toolbox, a white-box implementation in the Chow et al.\u27s framework has complexity at most $O\left(\min\left\{ \tfrac{2^{2m}}{m}\cdot n^{m+4}, n\log n \cdot 2^{n/2}\right\}\right)$ within reasonable storage, which is much less than $2^n$. To overcome this, we introduce an idea that obfuscates two AES-128 ciphers at once with input/output encoding on 256 bits. To reduce storage, we use a sparse unsplit input encoding. As a result, our white-box AES implementation has up to 110-bit security against our toolbox, close to that of the original cipher. More generally, we may consider a white-box implementation on the concatenation of $t$ ciphertexts to increase security

Biochemical Markers as Predictors of In-Hospital Mortality in Patients with Severe Trauma: A Retrospective Cohort Study

Background Initial evaluation of injury severity in trauma patients is an important and challenging task. We aimed to assess whether easily measurable biochemical parameters (hemoglobin, pH, and prothrombin time/international normalized ratio [PT/INR]) can predict in-hospital mortality in patients with severe trauma. Methods This retrospective study involved review of the medical records of 315 patients with severe trauma and an injury severity score >15 who were managed at Gyeongsang National University Hospital between January 2005 and December 2015. We extracted the following data: in-hospital mortality, injury severity score, and initial hemoglobin level, pH, and PT/INR. The predictive values of these variables were compared using receiver operation characteristic curves. Results Of the 315 patients, 72 (22.9%) died. The in-hospital mortality rates of patients with hemoglobin levels <8.4 g/dl and ≥8.4 g/dl were 49.8% and 9.9%, respectively (P < 0.001). At a cutoff hemoglobin level of 8.4 g/dl, the sensitivity and specificity values for mortality were 81.9% and 86.4%, respectively. At a pH cutoff of 7.25, the sensitivity and specificity values for mortality were 66.7% and 77.8%, respectively; 66.7% of patients with a pH <7.25 died versus 22.2% with a pH ≥7.25 (P < 0.001). The in-hospital mortality rates for patients with PT/INR values ≥1.4 and <1.4 were 37.5% and 16%, respectively (P < 0.001; sensitivity, 37.5%; specificity, 84%). Conclusions Using the suggested cutoff values, hemoglobin level, pH, and PT/INR can simply and easily be used to predict in-hospital mortality in patients with severe trauma

Intracellular gallium nitride microrod laser

We report laser emission from gallium nitride (GaN) microrods that are introduced into mammalian cells and the application of these microrods for cell labeling. GaN microrods were grown on graphene-coated SiO2/Si substrates by metal-organic vapor phase epitaxy. The GaN microrods are easily detached from the substrates because of the weakness of the van der Waals forces between GaN and graphene. The uptake of microrods into HeLa cells via endocytosis and viability after uptake were investigated. Normal cellular activities, including migration and division, were observed over 2 weeks in culture. Furthermore, the photoluminescence spectra of the internalized microrods exhibited sharp laser emission peaks with a low lasing threshold of 270kW/cm(2)

A differential risk assessment and decision model for Transarterial chemoembolization in hepatocellular carcinoma based on hepatic function

Background The decision of transarterial chemoembolization (TACE) initiation and/or repetition remains challenging in patients with unresectable hepatocellular carcinoma (HCC). The aim was to develop a prognostic scoring system to guide TACE initiation/repetition. Methods A total of 597 consecutive patients who underwent TACE as their initial treatment for unresectable HCC were included. We derived a prediction model using independent risk factors for overall survival (OS), which was externally validated in an independent cohort (n = 739). Results Independent risk factors of OS included Albumin-bilirubin (ALBI) grade, maximal tumor size, alpha-fetoprotein, and tumor response to initial TACE, which were used to develop a scoring system (ASAR). C-index values for OS were 0.733 (95% confidence interval [CI] = 0.570–0.871) in the derivation, 0.700 (95% CI = 0.445–0.905) in the internal validation, and 0.680 (95% CI = 0.652–0.707) in the external validation, respectively. Patients with ASAR< 4 showed significantly longer OS than patients with ASAR≥4 in all three datasets (all P < 0.001). Among Child-Pugh class B patients, a modified model without TACE response, i.e., ASA(R), discriminated OS with a c-index of 0.788 (95% CI, 0.703–0.876) in the derivation, and 0.745 (95% CI, 0.646–0.862) in the internal validation, and 0.670 (95% CI, 0.605–0.725) in the external validation, respectively. Child-Pugh B patients with ASA(R) < 4 showed significantly longer OS than patients with ASA(R) ≥ 4 in all three datasets (all P < 0.001). Conclusions ASAR provides refined prognostication for repetition of TACE in patients with unresectable HCC. For Child-Pugh class B patients, a modified model with baseline factors might guide TACE initiation

Guidelines for the use and interpretation of assays for monitoring autophagy (3rd edition)

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is that there is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure fl ux through the autophagy pathway (i.e., the complete process including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defi ned as increased autophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium ) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the fi eld understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in many cases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as for reviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multiple assays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation it is imperative to delete or knock down more than one autophagy-related gene. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways so not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular autophagy assays, we hope to encourage technical innovation in the field

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong