34,157 research outputs found

    Role based behavior analysis

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    Tese de mestrado, Segurança InformĂĄtica, Universidade de Lisboa, Faculdade de CiĂȘncias, 2009Nos nossos dias, o sucesso de uma empresa depende da sua agilidade e capacidade de se adaptar a condiçÔes que se alteram rapidamente. Dois requisitos para esse sucesso sĂŁo trabalhadores proactivos e uma infra-estrutura ĂĄgil de Tecnologias de InformacĂŁo/Sistemas de Informação (TI/SI) que os consiga suportar. No entanto, isto nem sempre sucede. Os requisitos dos utilizadores ao nĂ­vel da rede podem nao ser completamente conhecidos, o que causa atrasos nas mudanças de local e reorganizaçÔes. AlĂ©m disso, se nĂŁo houver um conhecimento preciso dos requisitos, a infraestrutura de TI/SI poderĂĄ ser utilizada de forma ineficiente, com excessos em algumas ĂĄreas e deficiĂȘncias noutras. Finalmente, incentivar a proactividade nĂŁo implica acesso completo e sem restriçÔes, uma vez que pode deixar os sistemas vulnerĂĄveis a ameaças externas e internas. O objectivo do trabalho descrito nesta tese Ă© desenvolver um sistema que consiga caracterizar o comportamento dos utilizadores do ponto de vista da rede. Propomos uma arquitectura de sistema modular para extrair informação de fluxos de rede etiquetados. O processo Ă© iniciado com a criação de perfis de utilizador a partir da sua informação de fluxos de rede. Depois, perfis com caracterĂ­sticas semelhantes sĂŁo agrupados automaticamente, originando perfis de grupo. Finalmente, os perfis individuais sĂŁo comprados com os perfis de grupo, e os que diferem significativamente sĂŁo marcados como anomalias para anĂĄlise detalhada posterior. Considerando esta arquitectura, propomos um modelo para descrever o comportamento de rede dos utilizadores e dos grupos. Propomos ainda mĂ©todos de visualização que permitem inspeccionar rapidamente toda a informação contida no modelo. O sistema e modelo foram avaliados utilizando um conjunto de dados reais obtidos de um operador de telecomunicaçÔes. Os resultados confirmam que os grupos projectam com precisĂŁo comportamento semelhante. AlĂ©m disso, as anomalias foram as esperadas, considerando a população subjacente. Com a informação que este sistema consegue extrair dos dados em bruto, as necessidades de rede dos utilizadores podem sem supridas mais eficazmente, os utilizadores suspeitos sĂŁo assinalados para posterior anĂĄlise, conferindo uma vantagem competitiva a qualquer empresa que use este sistema.In our days, the success of a corporation hinges on its agility and ability to adapt to fast changing conditions. Proactive workers and an agile IT/IS infrastructure that can support them is a requirement for this success. Unfortunately, this is not always the case. The user’s network requirements may not be fully understood, which slows down relocation and reorganization. Also, if there is no grasp on the real requirements, the IT/IS infrastructure may not be efficiently used, with waste in some areas and deficiencies in others. Finally, enabling proactivity does not mean full unrestricted access, since this may leave the systems vulnerable to outsider and insider threats. The purpose of the work described on this thesis is to develop a system that can characterize user network behavior. We propose a modular system architecture to extract information from tagged network flows. The system process begins by creating user profiles from their network flows’ information. Then, similar profiles are automatically grouped into clusters, creating role profiles. Finally, the individual profiles are compared against the roles, and the ones that differ significantly are flagged as anomalies for further inspection. Considering this architecture, we propose a model to describe user and role network behavior. We also propose visualization methods to quickly inspect all the information contained in the model. The system and model were evaluated using a real dataset from a large telecommunications operator. The results confirm that the roles accurately map similar behavior. The anomaly results were also expected, considering the underlying population. With the knowledge that the system can extract from the raw data, the users network needs can be better fulfilled, the anomalous users flagged for inspection, giving an edge in agility for any company that uses it

    High performance computation of landscape genomic models integrating local indices of spatial association

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    Since its introduction, landscape genomics has developed quickly with the increasing availability of both molecular and topo-climatic data. The current challenges of the field mainly involve processing large numbers of models and disentangling selection from demography. Several methods address the latter, either by estimating a neutral model from population structure or by inferring simultaneously environmental and demographic effects. Here we present SamÎČ\betaada, an integrated approach to study signatures of local adaptation, providing rapid processing of whole genome data and enabling assessment of spatial association using molecular markers. Specifically, candidate loci to adaptation are identified by automatically assessing genome-environment associations. In complement, measuring the Local Indicators of Spatial Association (LISA) for these candidate loci allows to detect whether similar genotypes tend to gather in space, which constitutes a useful indication of the possible kinship relationship between individuals. In this paper, we also analyze SNP data from Ugandan cattle to detect signatures of local adaptation with SamÎČ\betaada, BayEnv, LFMM and an outlier method (FDIST approach in Arlequin) and compare their results. SamÎČ\betaada is an open source software for Windows, Linux and MacOS X available at \url{http://lasig.epfl.ch/sambada}Comment: 1 figure in text, 1 figure in supplementary material The structure of the article was modified and some explanations were updated. The methods and results presented are the same as in the previous versio

    Optical Properties of the Ultraluminous X-ray Source Holmberg IX X-1 and its Stellar Environment

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    Holmberg IX X-1 is an archetypal ultraluminous X-ray source (ULX). Here we study the properties of the optical counterpart and of its stellar environment using optical data from SUBARU/Faint Object Camera and Spectrograph,GEMINI/GMOS-N and Hubble Space Telescope (HST)/Advanced Camera for Surveys, as well as simultaneous Chandra X-ray data. The V ~ 22.6 spectroscopically identified optical counterpart is part of a loose cluster with an age <~ 20 Myr. Consequently, the mass upper limit on individual stars in the association is about 20 M_sun. The counterpart is more luminous than the other stars of the association, suggesting a non-negligible optical contribution from the accretion disk. An observed UV excess also points to non-stellar light similar to X-ray active low-mass X-ray binaries. A broad HeII4686 emission line identified in the optical spectrum of the ULX further suggests optical light from X-ray reprocessing in the accretion disk. Using stellar evolutionary tracks, we have constrained the mass of the counterpart to be >~ 10 M_sun, even if the accretion disk contributes significantly to the optical luminosity. Comparison of the photometric properties of the counterpart with binary models show that the donor may be more massive, >~ 25 M_sun, with the ULX system likely undergoing case AB mass transfer. Finally, the counterpart exhibits photometric variability of 0.14 mag between two HST observations separated by 50 days which could be due to ellipsoidal variations and/or disk reprocessing of variable X-ray emission.Comment: 14 pages, 14 figures, accepted for publication in Ap

    An SDI for the GIS-education at the UGent Geography Department

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    The UGent Geography Department (GD) (ca. 200 students; 10 professors) has been teaching GIS since the mid 90’s. Ever since, GIS has evolved from Geographic Information Systems, to GIScience, to GIServices; implying that a GIS specialist nowadays has to deal with more than just desktop GIS. Knowledge about the interaction between different components of an SDI (spatial data, technologies, laws and policies, people and standards) is crucial for a graduated Master student. For its GIS education, the GD has until recently been using different sources of datasets, which were stored in a non-centralized system. In conformity with the INSPIRE Directive and the Flemish SDI Decree, the GD aims to set-up its own SDI using free and open source software components, to improve the management, user-friendliness, copyright protection and centralization of datasets and the knowledge of state of the art SDI structure and technology. The central part of the system is a PostGIS-database in which both staff and students can create and share information stored in a multitude of tables and schemas. A web-based application facilitates upper-level management of the database for administrators and staff members. Exercises in various courses not only focus on accessing and handling data from the SDI through common GIS-applications as QuantumGIS or GRASS, but also aim at familiarizing students with the set-up of widely used SDI-elements as WMS, WFS and WCS services. The (dis)advantages of the new SDI will be tested in a case study in which the workflow of a typical ‘GIS Applications’ exercise is elaborated. By solving a problem of optimal location, students interact in various ways with geographic data. A comparison is made between the situation before and after the implementation of the SDI

    Landscape attributes governing local transmission of an endemic zoonosis: rabies virus in domestic dogs

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    Landscape heterogeneity plays an important role in disease spread and persistence, but quantifying landscape influences and their scale dependence is challenging. Studies have focused on how environmental features or global transport networks influence pathogen invasion and spread, but their influence on local transmission dynamics that underpin the persistence of endemic diseases remains unexplored. Bayesian phylogeographic frameworks that incorporate spatial heterogeneities are promising tools for analysing linked epidemiological, environmental and genetic data. Here, we extend these methodological approaches to decipher the relative contribu- tion and scale-dependent effects of landscape influences on the transmission of endemic rabies virus in Serengeti district, Tanzania (area ~4,900 km2). Utilizing detailed epidemiological data and 152 complete viral genomes collected between 2004 and 2013, we show that the localized presence of dogs but not their density is the most important determinant of diffusion, implying that culling will be ineffec- tive for rabies control. Rivers and roads acted as barriers and facilitators to viral spread, respectively, and vaccination impeded diffusion despite variable annual cov- erage. Notably, we found that landscape effects were scale-dependent: rivers were barriers and roads facilitators on larger scales, whereas the distribution of dogs was important for rabies dispersal across multiple scales. This nuanced understanding of the spatial processes that underpin rabies transmission can be exploited for targeted control at the scale where it will have the greatest impact. Moreover, this research demonstrates how current phylogeographic frameworks can be adapted to improve our understanding of endemic disease dynamics at different spatial scales
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