Implementing the ADVISE Security Modeling Formalism in Möbius

Abstract-The ADversary VIew Security Evaluation (ADVISE) model formalism provides a system security model from the perspective of an adversary. An ADVISE atomic model consists of an attack execution graph (AEG) composed of attack steps, system state variables, and attack goals, as well as an adversary profile that defines the abilities and interests of a particular adversary. The ADVISE formalism has been implemented as a Möbius atomic model formalism in order to leverage the existing set of mature modeling formalisms and solution techniques offered by Möbius. This tool paper explains the ADVISE implementation in Möbius and provides technical details for Möbius users who want to use ADVISE either alone or in combination with other modeling formalisms provided by Möbius

Spin states of zigzag-edged Mobius graphene nanoribbons from first principles

Mobius graphene nanoribbons have only one edge topologically. How the magnetic structures, previously associated with the two edges of zigzag-edged flat nanoribbons or cyclic nanorings, would change for their Mobius counterparts is an intriguing question. Using spin-polarized density functional theory, we shed light on this question. We examine spin states of zigzag-edged Mobius graphene nanoribbons (ZMGNRs) with different widths and lengths. We find a triplet ground state for a Mobius cyclacene, while the corresponding two-edged cyclacene has an open-shell singlet ground state. For wider ZMGNRs, the total magnetization of the ground state is found to increase with the ribbon length. For example, a quintet ground state is found for a ZMGNR. Local magnetic moments on the edge carbon atoms form domains of majority and minor spins along the edge. Spins at the domain boundaries are found to be frustrated. Our findings show that the Mobius topology (i.e., only one edge) causes ZMGNRs to favor one spin over the other, leading to a ground state with non-zero total magnetization.Comment: 17 pages, 4 figure

Stochastic modelling of the effects of interdependencies between critical infrastructure

An approach to Quantitative Interdependency Analysis, in the context of Large Complex Critical Infrastructures, is presented in this paper. A Discrete state–space, Continuous–time, Stochastic Process models the operation of critical infrastructure, taking interdependencies into account. Of primary interest are the implications of both model detail (that is, level of model abstraction) and model parameterisation for the study of dependencies. Both of these factors are observed to affect the distribution of cascade–sizes within and across infrastructure

Recent advances in directional statistics

Mainstream statistical methodology is generally applicable to data observed in Euclidean space. There are, however, numerous contexts of considerable scientific interest in which the natural supports for the data under consideration are Riemannian manifolds like the unit circle, torus, sphere and their extensions. Typically, such data can be represented using one or more directions, and directional statistics is the branch of statistics that deals with their analysis. In this paper we provide a review of the many recent developments in the field since the publication of Mardia and Jupp (1999), still the most comprehensive text on directional statistics. Many of those developments have been stimulated by interesting applications in fields as diverse as astronomy, medicine, genetics, neurology, aeronautics, acoustics, image analysis, text mining, environmetrics, and machine learning. We begin by considering developments for the exploratory analysis of directional data before progressing to distributional models, general approaches to inference, hypothesis testing, regression, nonparametric curve estimation, methods for dimension reduction, classification and clustering, and the modelling of time series, spatial and spatio-temporal data. An overview of currently available software for analysing directional data is also provided, and potential future developments discussed.Comment: 61 page

Hyperbolic Interaction Model For Hierarchical Multi-Label Classification

Different from the traditional classification tasks which assume mutual exclusion of labels, hierarchical multi-label classification (HMLC) aims to assign multiple labels to every instance with the labels organized under hierarchical relations. Besides the labels, since linguistic ontologies are intrinsic hierarchies, the conceptual relations between words can also form hierarchical structures. Thus it can be a challenge to learn mappings from word hierarchies to label hierarchies. We propose to model the word and label hierarchies by embedding them jointly in the hyperbolic space. The main reason is that the tree-likeness of the hyperbolic space matches the complexity of symbolic data with hierarchical structures. A new Hyperbolic Interaction Model (HyperIM) is designed to learn the label-aware document representations and make predictions for HMLC. Extensive experiments are conducted on three benchmark datasets. The results have demonstrated that the new model can realistically capture the complex data structures and further improve the performance for HMLC comparing with the state-of-the-art methods. To facilitate future research, our code is publicly available

How round is a protein? Exploring protein structures for globularity using conformal mapping.

We present a new algorithm that automatically computes a measure of the geometric difference between the surface of a protein and a round sphere. The algorithm takes as input two triangulated genus zero surfaces representing the protein and the round sphere, respectively, and constructs a discrete conformal map f between these surfaces. The conformal map is chosen to minimize a symmetric elastic energy E S (f) that measures the distance of f from an isometry. We illustrate our approach on a set of basic sample problems and then on a dataset of diverse protein structures. We show first that E S (f) is able to quantify the roundness of the Platonic solids and that for these surfaces it replicates well traditional measures of roundness such as the sphericity. We then demonstrate that the symmetric elastic energy E S (f) captures both global and local differences between two surfaces, showing that our method identifies the presence of protruding regions in protein structures and quantifies how these regions make the shape of a protein deviate from globularity. Based on these results, we show that E S (f) serves as a probe of the limits of the application of conformal mapping to parametrize protein shapes. We identify limitations of the method and discuss its extension to achieving automatic registration of protein structures based on their surface geometry

Möbius Geometry and Cyclidic Nets: A Framework for Complex Shape Generation

International audienceFree-form architecture challenges architects, engineers and builders. The geometrical rationalization of complex structures requires sophisticated tools. To this day, two frameworks are commonly used: NURBS modeling and mesh-based approaches. The authors propose an alternative modeling framework called generalized cyclidic nets that automatically yields optimal geometrical properties for the façade and the structure. This framework uses a base circular mesh and Dupin cyclides, which are natural objects of the geometry of circles in space, also known as Möbius geometry. This paper illustrates how new shapes can be generated from generalized cyclidic nets. Finally, it is demonstrated that this framework gives a simple method to generate curved-creases on free-forms. These findings open new perspectives for structural design of complex shells

List of requirements on formalisms and selection of appropriate tools

This deliverable reports on the activities for the set-up of the modelling environments for the evaluation activities of WP5. To this objective, it reports on the identified modelling peculiarities of the electric power infrastructure and the information infrastructures and of their interdependencies, recalls the tools that have been considered and concentrates on the tools that are, and will be, used in the project: DrawNET, DEEM and EPSys which have been developed before and during the project by the partners, and M\uf6bius and PRISM, developed respectively at the University of Illinois at Urbana Champaign and at the University of Birmingham (and recently at the University of Oxford)