Methodologies to develop quantitative risk evaluation metrics

The goal of this work is to advance a new methodology to measure a severity cost for each host using the Common Vulnerability Scoring System (CVSS) based on base, temporal and environmental metrics by combining related sub-scores to produce a unique severity cost by modeling the problem's parameters in to a mathematical framework. We build our own CVSS Calculator using our equations to simplify the calculations of the vulnerabilities scores and to benchmark with other models. We design and develop a new approach to represent the cost assigned to each host by dividing the scores of the vulnerabilities to two main levels of privileges, user and root, and we classify these levels into operational levels to identify and calculate the severity cost of multi steps vulnerabilities. Finally we implement our framework on a simple network, using Nessus scanner as tool to discover known vulnerabilities and to implement the results to build and represent our cost centric attack graph

Allelopathic interactions of marine diatoms

Als eukaryotisches Phytoplankton bilden Diatomeen die Grundlage des marinen Nahrungsnetzes. Diese Diatomeengemeinschaften werden nicht nur von abiotischen Faktoren wie Temperatur und Nährstoffkonzentration geformt, sondern vielmehr auch von biotischen Faktoren mitbestimmt. Bei diesen biotischen Faktoren spielen Interaktionen von Diatomeen mit Bakterien und anderen Diatomeenarten eine herausragende Rolle. Trotz dieser immensen Bedeutung existiert nur ein limitiertes Verständnis dieser Interaktionen. Ziel dieser Arbeit war es Diatomeen-Diatomeen wie auch Diatomeen-Bakterien Interaktionen zu untersuchen. Hierbei zeigte sich, dass polyungesättigte Aldehyde (PUA), ausgeschieden von Algen wie Skeletonema, keine regulierende Funktion auf die Bakteriengemeinschaft besitzen. Im Gegenzug konnte ich zeigen, dass die Bakterien Kordia algicida Proteasen benutzen um Algen wie Skeletonema zu inhibieren. Die Ausschüttung der Proteasen, welche Spezies-spezifisch wirken, erfolgt dabei über einen Quorum Sensing regulierten Mechanismus. Auf der Seite der Diatomeen-Diatomeen Interaktionen konnte Bromocyan als neuer aktiver Naturstoff isoliert werden. Für beide Interaktionsarten konnte ich erstmalig ein auf Massenspektrometrie basierender Metabolomics Ansatz anwenden. Durch Ko-Kultivierungen zeigte sich, dass das extra- und intrazelluläre metabolische Profil von der Präsenz anderer Algen beziehungsweise Bakterien abhängig ist. Somit ergibt sich ein komplexes Bild von den Interaktionsmöglichkeiten von Diatomeen

Survivability : A Unifiying Concept for the Transient Resilience of Deterministic Dynamical Systems

16 pagesNon peer reviewedPreprin

Survivability of Deterministic Dynamical Systems

The notion of a part of phase space containing desired (or allowed) states of a dynamical system is important in a wide range of complex systems research. It has been called the safe operating space, the viability kernel or the sunny region. In this paper we define the notion of survivability: Given a random initial condition, what is the likelihood that the transient behaviour of a deterministic system does not leave a region of desirable states. We demonstrate the utility of this novel stability measure by considering models from climate science, neuronal networks and power grids. We also show that a semi-analytic lower bound for the survivability of linear systems allows a numerically very efficient survivability analysis in realistic models of power grids. Our numerical and semi-analytic work underlines that the type of stability measured by survivability is not captured by common asymptotic stability measures.Comment: 21 pages, 6 figure

Improving Unsupervised Defect Segmentation by Applying Structural Similarity to Autoencoders

Convolutional autoencoders have emerged as popular methods for unsupervised defect segmentation on image data. Most commonly, this task is performed by thresholding a pixel-wise reconstruction error based on an $\ell^p$ distance. This procedure, however, leads to large residuals whenever the reconstruction encompasses slight localization inaccuracies around edges. It also fails to reveal defective regions that have been visually altered when intensity values stay roughly consistent. We show that these problems prevent these approaches from being applied to complex real-world scenarios and that it cannot be easily avoided by employing more elaborate architectures such as variational or feature matching autoencoders. We propose to use a perceptual loss function based on structural similarity which examines inter-dependencies between local image regions, taking into account luminance, contrast and structural information, instead of simply comparing single pixel values. It achieves significant performance gains on a challenging real-world dataset of nanofibrous materials and a novel dataset of two woven fabrics over the state of the art approaches for unsupervised defect segmentation that use pixel-wise reconstruction error metrics

Impedance generalization for plasmonic waveguides beyond the lumped circuit model

We analytically derive a rigorous expression for the relative impedance ratio between two photonic structures based on their electromagnetic interaction. Our approach generalizes the physical meaning of the impedance to a measure for the reciprocity-based overlap of eigenmodes. The consistence with known cases in the radiofrequency and optical domain is shown. The analysis reveals where the applicability of simple circuit parameters ends and how the impedance can be interpreted beyond this point. We illustrate our approach by successfully describing a Bragg reflector that terminates an insulator-metal-insulator plasmonic waveguide in the near-infrared by our mpedance concept

A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph Matching

We study the quadratic assignment problem, in computer vision also known as graph matching. Two leading solvers for this problem optimize the Lagrange decomposition duals with sub-gradient and dual ascent (also known as message passing) updates. We explore s direction further and propose several additional Lagrangean relaxations of the graph matching problem along with corresponding algorithms, which are all based on a common dual ascent framework. Our extensive empirical evaluation gives several theoretical insights and suggests a new state-of-the-art any-time solver for the considered problem. Our improvement over state-of-the-art is particularly visible on a new dataset with large-scale sparse problem instances containing more than 500 graph nodes each.Comment: Added acknowledgment