Feature-Guided Black-Box Safety Testing of Deep Neural Networks

Despite the improved accuracy of deep neural networks, the discovery of adversarial examples has raised serious safety concerns. Most existing approaches for crafting adversarial examples necessitate some knowledge (architecture, parameters, etc.) of the network at hand. In this paper, we focus on image classifiers and propose a feature-guided black-box approach to test the safety of deep neural networks that requires no such knowledge. Our algorithm employs object detection techniques such as SIFT (Scale Invariant Feature Transform) to extract features from an image. These features are converted into a mutable saliency distribution, where high probability is assigned to pixels that affect the composition of the image with respect to the human visual system. We formulate the crafting of adversarial examples as a two-player turn-based stochastic game, where the first player's objective is to minimise the distance to an adversarial example by manipulating the features, and the second player can be cooperative, adversarial, or random. We show that, theoretically, the two-player game can con- verge to the optimal strategy, and that the optimal strategy represents a globally minimal adversarial image. For Lipschitz networks, we also identify conditions that provide safety guarantees that no adversarial examples exist. Using Monte Carlo tree search we gradually explore the game state space to search for adversarial examples. Our experiments show that, despite the black-box setting, manipulations guided by a perception-based saliency distribution are competitive with state-of-the-art methods that rely on white-box saliency matrices or sophisticated optimization procedures. Finally, we show how our method can be used to evaluate robustness of neural networks in safety-critical applications such as traffic sign recognition in self-driving cars.Comment: 35 pages, 5 tables, 23 figure

Cosmic ray modulation in a random anisotropic magnetic field

Inhomogeneities of the interplanetary magnetic field can be divided into small scale and large scale ones as may be required by the character of the problem of cosmic ray (CR) propagation. CR propagation in stochastic magnetic fields is of diffusion character. The main contribution into the scattering of CR particles is made by their interaction with inhomogeneities of the magnetic field H which have characteristic dimensions 1 of the order of Larmor radius R=cp/eH of particle (p is the absolute value of particle momentum, e is particle charge, c is velocity of light). Scattering of particles on such inhomogeneities leads to their diffusion mostly along a magnetic field with characteristic dimensions of variation in space exceeding the mean free path

Warped Domain Wall Fermions

We consider Kaplan's domain wall fermions in the presence of an Anti-de Sitter (AdS) background in the extra dimension. Just as in the flat space case, in a completely vector-like gauge theory defined after discretizing this extra dimension, the spectrum contains a very light charged fermion whose chiral components are localized at the ends of the extra dimensional interval. The component on the IR boundary of the AdS space can be given a large mass by coupling it to a neutral fermion via the Higgs mechanism. In this theory, gauge invariance can be restored either by taking the limit of infinite proper length of the extra dimension or by reducing the AdS curvature radius towards zero. In the latter case, the Kaluza-Klein modes stay heavy and the resulting classical theory approaches a chiral gauge theory, as we verify numerically. Potential difficulties for this approach could arise from the coupling of the longitudinal mode of the light gauge boson, which has to be treated non-perturbatively

NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems

This paper presents the Neural Network Verification (NNV) software tool, a set-based verification framework for deep neural networks (DNNs) and learning-enabled cyber-physical systems (CPS). The crux of NNV is a collection of reachability algorithms that make use of a variety of set representations, such as polyhedra, star sets, zonotopes, and abstract-domain representations. NNV supports both exact (sound and complete) and over-approximate (sound) reachability algorithms for verifying safety and robustness properties of feed-forward neural networks (FFNNs) with various activation functions. For learning-enabled CPS, such as closed-loop control systems incorporating neural networks, NNV provides exact and over-approximate reachability analysis schemes for linear plant models and FFNN controllers with piecewise-linear activation functions, such as ReLUs. For similar neural network control systems (NNCS) that instead have nonlinear plant models, NNV supports over-approximate analysis by combining the star set analysis used for FFNN controllers with zonotope-based analysis for nonlinear plant dynamics building on CORA. We evaluate NNV using two real-world case studies: the first is safety verification of ACAS Xu networks and the second deals with the safety verification of a deep learning-based adaptive cruise control system

Denominators of Eisenstein cohomology classes for GL_2 over imaginary quadratic fields

We study the arithmetic of Eisenstein cohomology classes (in the sense of G. Harder) for symmetric spaces associated to GL_2 over imaginary quadratic fields. We prove in many cases a lower bound on their denominator in terms of a special L-value of a Hecke character providing evidence for a conjecture of Harder that the denominator is given by this L-value. We also prove under some additional assumptions that the restriction of the classes to the boundary of the Borel-Serre compactification of the spaces is integral. Such classes are interesting for their use in congruences with cuspidal classes to prove connections between the special L-value and the size of the Selmer group of the Hecke character.Comment: 37 pages; strengthened integrality result (Proposition 16), corrected statement of Theorem 3, and revised introductio

Effect of fruit and vegetable concentrates on endothelial function in metabolic syndrome: A randomized controlled trial

<p>Abstract</p> <p>Background and Objective</p> <p>Dehydrated fruit and vegetable concentrates provide an accessible form of phytonutrient supplementation that may offer cardioprotective effects. This study assessed the effects of two blends of encapsulated juice powder concentrates (with and without added berry powders) on endothelial function in persons with metabolic syndrome, a risk factor for type 2 diabetes and cardiovascular disease.</p> <p>Methods</p> <p>Randomized, double blind, placebo controlled crossover clinical trial with three treatment arms. 64 adults with metabolic syndrome were enrolled and received 8-week sequences of each blend of the concentrates and placebo. The primary outcome measure was change in endothelial function (assessed as flow-mediated dilatation of the brachial artery) 2 hr after consuming a 75 g glucose load, after 8-weeks of daily consumption (sustained) or 2 hr after consumption of a single dose (acute). Secondary outcome measures included plasma glucose, serum insulin, serum lipids, and body weight.</p> <p>Results</p> <p>No significant between-group differences in endothelial function with daily treatment for 8 weeks were seen. No other significant treatment effects were discerned in glucose, insulin, lipids, and weight.</p> <p>Conclusion</p> <p>Encapsulated fruit and vegetable juice powder concentrates did not alter insulin or glucose measures in this sample of adults with metabolic syndrome.</p> <p>Trial Registration</p> <p>clinicaltrials.gov <a href="http://www.clinicaltrials.gov/ct2/show/NCT01224743">NCT01224743</a></p

Electronic structure of and Quantum size effect in III-V and II-VI semiconducting nanocrystals using a realistic tight binding approach

We analyze the electronic structure of group III-V semiconductors obtained within full potential linearized augmented plane wave (FP-LAPW) method and arrive at a realistic and minimal tight-binding model, parameterized to provide an accurate description of both valence and conduction bands. It is shown that cation sp3 - anion sp3d5 basis along with the next nearest neighbor model for hopping interactions is sufficient to describe the electronic structure of these systems over a wide energy range, obviating the use of any fictitious s* orbital, employed previously. Similar analyses were also performed for the II-VI semiconductors, using the more accurate FP-LAPW method compared to previous approaches, in order to enhance reliability of the parameter values. Using these parameters, we calculate the electronic structure of III-V and II-VI nanocrystals in real space with sizes ranging upto about 7 nm in diameter, establishing a quantitatively accurate description of the band-gap variation with sizes for the various nanocrystals by comparing with available experimental results from the literature.Comment: 28 pages, 8 figures, Accepted for publication in Phys. Rev.

Gauge Threshold Corrections in Warped Geometry

We discuss the Kaluza-Klein threshold correction to low energy gauge couplings in theories with warped extra-dimension, which might be crucial for the gauge coupling unification when the warping is sizable. Explicit expressions of one-loop thresholds are derived for generic 5D gauge theory on a slice of AdS_5, where some of the bulk gauge symmetries are broken by orbifold boundary conditions and/or by bulk Higgs vacuum values. Effects of the mass mixing between the bulk fields with different orbifold parities are included as such mixing is required in some class of realistic warped unification models.Comment: 33 pages, 1 figure, 6 tables, invited contribution to New Journal of Physics Focus Issue on 'Extra Space Dimensions

Textual analysis of internal medicine residency personal statements: themes and gender differences

Context Applicants to US residency training programmes are required to submit a personal statement, the content of which is flexible but often requires them to describe their career goals and aspirations. Despite their importance, no systematic research has explored common themes and gender differences inherent to these statements. Objectives This study was conducted to analyse US applicants’ Electronic Residency Application Service (ERAS) personal statements using two automated textual analysis programs, and to assess for common themes and gender-associated differences. Methods A retrospective cohort study of 2138 personal statements (containing 1 485 255 words) from candidates from 377 national and international medical schools applying to US internal medicine (IM) residency programmes through ERAS was conducted. A mathematical analysis of text segments using a recursive algorithm was performed; two different specifications of the text segments were used to conduct an internal validation. Results Five statistically significant thematic classes were identified through independent review by the researchers. These were best defined as referring to: the appeal of the residency programme; memorable patients; health care as public policy; research and academia, and family inspiration. Some themes were common to all applications. However, important gender-specific differences were identified. Notably, men were more likely to describe personal attributes and to self-promote, whereas women more frequently expressed the communicative and team-based aspects of doctoring. The results were externally validated using a second software program. Although these data comprise part of the national pool, they represent applicants to a single specialty at a single institution. Conclusions By applying textual analysis to material derived from a national cohort, we identified common narrative themes in the personal statements of future US physicians, noting differences between men and women. Together, these data provide novel insight into the dominant discourse of doctoring in this generation of students applying for further training in US IM residency programmes, and depict a diverse group of applicants with multiple motivations, desires and goals. Furthermore, differences seen between men and women add to the growing understanding of bias in medical education. Training programmes may benefit by adapting curricula to foster such diverse interests

Fermions and Loops on Graphs. II. Monomer-Dimer Model as Series of Determinants

We continue the discussion of the fermion models on graphs that started in the first paper of the series. Here we introduce a Graphical Gauge Model (GGM) and show that : (a) it can be stated as an average/sum of a determinant defined on the graph over $\mathbb{Z}_{2}$ (binary) gauge field; (b) it is equivalent to the Monomer-Dimer (MD) model on the graph; (c) the partition function of the model allows an explicit expression in terms of a series over disjoint directed cycles, where each term is a product of local contributions along the cycle and the determinant of a matrix defined on the remainder of the graph (excluding the cycle). We also establish a relation between the MD model on the graph and the determinant series, discussed in the first paper, however, considered using simple non-Belief-Propagation choice of the gauge. We conclude with a discussion of possible analytic and algorithmic consequences of these results, as well as related questions and challenges.Comment: 11 pages, 2 figures; misprints correcte