De la metafísica a la anarquía. El pensamiento político de Reiner Schürmann

El artículo pretende abordar el modo en el que la obra de Reiner Schürmann, a través de un original interpretación del pensamiento de Martin Heidegger, consigue desarrollar un tipo de filosofía política anárquica. Se intentará analizar, en la dispersa obra del filósofo holandés, la idea de anarquía como condición existencial, prestando especial atención al nexo entre el concepto de muerte de la metafísica y la posibilidad de una praxis política anárquica. El artículo se compone de tres partes: en la primera se examinará la noción de Ser y de “a priori práctico” en el trabajo de Schürmann. En la segunda se verá la diferencia entre el nihilismo del autor y el de Vattimo, y en la tercera, se profundizará en las consecuencias más propiamente políticas del pensamiento de Schürmann.

Data Reduction in Intrusion Alert Correlation

Network intrusion detection sensors are usually built around low level models of network traffic. This means that their output is of a similarly low level and as a consequence, is difficult to analyze. Intrusion alert correlation is the task of automating some of this analysis by grouping related alerts together. Attack graphs provide an intuitive model for such analysis. Unfortunately alert flooding attacks can still cause a loss of service on sensors, and when performing attack graph correlation, there can be a large number of extraneous alerts included in the output graph. This obscures the fine structure of genuine attacks and makes them more difficult for human operators to discern. This paper explores modified correlation algorithms which attempt to minimize the impact of this attack.

Strategic Alert Throttling for Intrusion Detection Systems

Network intrusion detection systems are themselves becoming targets of attackers. Alert flood attacks may be used to conceal malicious activity by hiding it among a deluge of false alerts sent by the attacker. Although these types of attacks are very hard to stop completely, our aim is to present techniques that improve alert throughput and capacity to such an extent that the resources required to successfully mount the attack become prohibitive. The key idea presented is to combine a token bucket filter with a realtime correlation algorithm. The proposed algorithm throttles alert output from the IDS when an attack is detected. The attack graph used in the correlation algorithm is used to make sure that alerts crucial to forming strategies are not discarded by throttling.

Information Fusion for Anomaly Detection with the Dendritic Cell Algorithm

Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system, providing the initial detection of pathogenic invaders. Research into this family of cells has revealed that they perform information fusion which directs immune responses. We have derived a Dendritic Cell Algorithm based on the functionality of these cells, by modelling the biological signals and differentiation pathways to build a control mechanism for an artificial immune system. We present algorithmic details in addition to experimental results, when the algorithm was applied to anomaly detection for the detection of port scans. The results show the Dendritic Cell Algorithm is successful at detecting port scans.

Immune System Approaches to Intrusion Detection - A Review

The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we review the algorithms used, the development of the systems and the outcome of their implementation. We provide an introduction and analysis of the key developments within this field, in addition to making suggestions for future research.

Integrating Innate and Adaptive Immunity for Intrusion Detection

Network Intrusion Detection Systems (NIDS) monitor a net- work with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDS’s rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to an intrusion detection problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

An Immune Network Intrusion Detection System Utilising Correlation Context

Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

Strategic Alert Throttling for Intrusion Detection Systems

Network intrusion detection systems are themselves becoming targets of attackers. Alert flood attacks may be used to conceal malicious activity by hiding it among a deluge of false alerts sent by the attacker. Although these types of attacks are very hard to stop completely, our aim is to present techniques that improve alert throughput and capacity to such an extent that the resources required to successfully mount the attack become prohibitive. The key idea presented is to combine a token bucket filter with a realtime correlation algorithm. The proposed algorithm throttles alert output from the IDS when an attack is detected. The attack graph used in the correlation algorithm is used to make sure that alerts crucial to forming strategies are not discarded by throttling.

Immune System Approaches to Intrusion Detection - A Review

The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we review the algorithms used, the development of the systems and the outcome of their implementation. We provide an introduction and analysis of the key developments within this field, in addition to making suggestions for future research.

An immune inspired Network Intrusion Detection System utilising correlation

Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

Real-time alert correlation with type graphs

The premise of automated alert correlation is to accept that false alerts from a low level intrusion detection system are inevitable and use attack models to explain the output in an understandable way. Several algorithms exist for this purpose which use attack graphs to model the ways in which attacks can be combined. These algorithms can be classified in to two broad categories namely scenario-graph approaches, which create an attack model starting from a vulnerability assessment and type-graph approaches which rely on an abstract model of the relations between attack types. Some research in to improving the efficiency of type-graph correlation has been carried out but this research has ignored the hypothesizing of missing alerts. Our work is to present a novel type-graph algorithm which unifies correlation and hypothesizing in to a single operation. Our experimental results indicate that the approach is extremely efficient in the face of intensive alerts and produces compact output graphs comparable to other techniques.

O design de moda e a indústria

Dissertação para obtenção do grau de Mestre em Design de Moda, apresentada na Universidade de Lisboa - Faculdade de Arquitetura.

Possibilities and problems of teaching the history of the present time through media and information literacy.

Le système éducatif encourage une histoire positiviste, ordonnée, unilatérale et universelle; par l´incorporation de le découpage chronologique de l´histoire en quatre étapes. Mais, est-ce qu´il serait posible que les élèves puissent étudier leur propre présent? Mon commuication poursuit d´exposer, comme Saab affirmait, le présent est “le point de départ et d´arrivée de l´enseignement de l´histoire détermine les allers et les retours au passé”. La façon d´approcher l´enseignement de l´histoire est confortable. Il n´y a pas de questions, il n´y a pas de discussions. Cette vision de l´histoire interprétée par l´homme blancoccidental-hétérosexuel s´inscrit dans le projet de la modernité du Siècle des Lumières. Par conséquent, cette histoire obvie que nous vivons dans una société postmoderne de la suspicion, de la pensée débile. En ce qui concerne la problématique autour de la pollution audiovisuelle et la façon dont les enseignants et les élèves sont quotidiennement confrontés à ce problème. Par conséquent, il est nécessaire de réfléchir à la question de l´enseignement de l´histoire quadripartite. Actuellement, les médias et les nouvelles technologies sont en train de changer la vie de l´humanité. Il est indispensable que l´élève connaisse son histoire presente et les scénarioshistoriques dans l´avenir. Je pense en la nécessité d´adopter une didactique de l’histoire presente et par conséquent, nous devons utiliser la maîtrise des médias et de l´information. Il faut une formation des enseignants que pose, comme Gadamer a dit: “le passé y le présent se trouvent par une négociation permanente”. Una formation des enseignants qui permette de comprendre et penser l´histoire future / les histoires futures. À mon avis, si les élèves comprennent la complexité de leur monde et leurs multiples visions, les élèves seront plus tolérantes et empathiques.

Funzioni di Matrici. Proprieta' e applicazione ai social networks

Teoria delle funzioni di matrici. Spiegazione del concetto di network, proprietà rilevanti rilevate attraverso determinate funzioni di matrici. Applicazione della teoria a due esempi di network reali.

Aplicación de estrategias innovadoras de E-Learning y autoevaluación en los ejercicios de intercomparación de los laboratorios de Química Analítica

La introducción de las Tecnologías Informáticas en los centros educativos de enseñanza universitaria, así como la penetración de Internet en la vida académica, nos ofrece todo un caudal de oportunidades para optimizar el proceso de enseñanza-aprendizaje y experimentar con nuevas formas de enseñanza, basadas en el manejo de las herramientas digitales. Estas nuevas prácticas en el aula, que se han ido desarrollando en los últimos años, potencian el aprendizaje constructivo y colaborativo entre los educandos haciendo que reflexionen acerca de sus ideas y de las de los demás. La introducción de las TICs en el marco educativo universitario ha modificado considerablemente no solo el modo de enseñanza/aprendizaje sino también en el contexto de la evaluación. Dentro del concepto de evaluación colaborativa, existe un gran número de trabajos y propuestas desde los inicios de las prácticas educativas formales en contextos virtuales. A pesar de esta presencia la evaluación colaborativa sigue siendo un campo por explorar debido a la dificultad que entraña, el extraer indicadores para la evaluación del aprendizaje mediante recursos virtual e-learning como foros, debates, u otras herramientas más complejas que conllevan el trabajo/aprendizaje colaborativo entre alumnos (grupos virtuales) como es el caso de las webQuest, Wikis, etc. Una ventaja metodológica es que la tecnología nos aporta la posibilidad no sólo de evaluar el producto colaborativo sino también el proceso. Este hecho es significativamente diferente del que ocurre en las prácticas presenciales que resulta de mucho interés para una verdadera evaluación formativa. El proyecto solicitado “Diseño y aplicación de estrategias innovadoras de evaluación colaborativa y autoevaluación e-learning en los ejercicios de intercomparación de los laboratorios de química analítica supondrá la implantación de metodologías activas y participativas orientadas a facilitar y mejorar el proceso de enseñanza-aprendizaje en general, y la innovación en estrategias de evaluación y de autoevaluación en particular, favoreciendo la participación de los alumnos en actividades formativas fuera del aula como parte fundamental de una docencia de calidad dentro del Espacio Europeo de Educación Superior (EEES). En concreto se utilizará como herramienta una webquest en la cual se desarrollarán tareas de evaluación colaborativa como la elaboración de una wiki, y un e-portafolio entre otras, de aplicación a distintas asignaturas del área de la química que implementan los ejercicios de intercomparación de los resultados obtenidos en los laboratorios de química analítica (implantado mediante proyectos de innovación). Estos ejercicios permiten que los estudiantes reciban información comparada de los resultados de su trabajo con el obtenido por otros estudiantes de su mismo nivel, motivándoles a trabajar lo mejor posible para obtener buenos resultados y que quede demostrado la calidad del trabajo realizado. La participación en estos ejercicios de intercomparación es un requisito contemplado en la norma UNE-EN-ISO 17025 para asegurar la competencia técnica necesaria para realizar ensayos de calidad y de forma fiable. Este proyecto está basado en la experiencia del equipo docente que forma parte de este proyecto en la implementación de varios proyectos de innovación que han logrado la implementación de los ejercicios de intercomparción en la Facultad de Químicas como un elemento diferenciador y de calidad de los Grados impartidos en la UCM.