Cibercrimen y ciberterrorismo : ¿exageración mediática o realidad?

La expansión de las tecnologías de la información y las comunicaciones (TIC) ha traído muchas ventajas, pero también algunos peligros. Son frecuentes hoy en día las noticias sobre delitos relacionados con las TIC. Se usa a menudo el término cibercrimen y el de ciberterrorismo pero, ¿realmente son una amenaza para la sociedad?. Este trabajo realiza un análisis del cibercrimen y el ciberterrorismo. Para ello se hace un estudio en profundidad desde distintos puntos de vista. En primer lugar se analizan varios aspectos básicos de la materia: el contexto en el que se desarrollan estas actividades, el ciberespacio y sus características, las ventajas que tiene el cibercrimen respecto a la delincuencia tradicional, características y ejemplos de ciberterrorismo y la importancia de la protección de las infraestructuras críticas. Luego se realiza un estudio del mundo del cibercrimen, en el cual se muestran los distintos tipos de cibercriminales, los actos delictivos, herramientas y técnicas más habituales usadas por el cibercrimen, la web profunda y la criptomoneda; se indican asimismo varios de los grupos criminales más conocidos y algunas de sus acciones, y se realiza un estudio de las consecuencias económicas del cibercrimen. Finalmente se hace un repaso a los medios legales que distintos países y organizaciones han establecido para combatir estos hechos delictivos. Para ello se analizan estrategias de seguridad de distinto tipo aprobadas en multitud de países de todo el mundo y los grupos operativos de respuesta (tanto los de tipo policial como los CSIRT/CERT), además de la legislación publicada para poder perseguir el cibercrimen y el ciberterrorismo, con especial atención a la legislación española. De esta manera, tras la lectura de este Proyecto se puede tener una visión global completa del mundo de la ciberdelincuencia y el ciberterrorismo. ABSTRACT. The expansion of Information and Communications Technology (ITC) has brought many benefits, but also some dangers. It is very usual nowadays to see news about ITC-related crimes. Terms like cyber crime and cyber terrorism are usually used but, are they really a big threat for our society?. This work analyzes cyber crime and cyber terrorism. To achieve it, a deep research under different points of view is made. First, basic aspects of the topic are analyzed: the context where these activities are carried out, cyber space and its features, benefits for cyber criminals with respect to traditional crime, characteristics and relevant examples of cyber terrorism, and importance of critical infrastructures protection. Then, a study about the world of cyber crime is made, analyzing the typology of different kinds of cyber criminals, the most common criminal acts, tools and techniques used by cyber crime, and the deep web and cryptocurrency. Some of the most known criminal groups and their activities are also explored, and the economic consequences of cyber crime are assessed. Finally, there is a review of the legal means used by countries and organizations to fight against these unlawful acts; this includes the analysis of several types of security strategies approved by countries all around the world, operational response groups (including law enforcement and CSIRT/CERT) and legislation to fight cyber crime and cyber terrorism, with special emphasis on Spanish legal rules. This way, a global, complete view of the world around cyber crime and cyber terrorism can be obtained after reading this work.

Urban Archaeology in Madrid. Experiences and Opportunities to Understand Historical City

In 2015, it will be thirty years since Spanish Historic Heritage Law from 1985 was approved. The results after three decades under this law are necessarily positive and witness how the complex autonomous regional legislation has been promoted, guided and organized in this Heritage field. In addition, the law enforcement has brought into the scene how the numerous public and private initiatives involved in caring, managing, protecting and restoring our cultural heritage have been channeled and regulated, as well as monitoring the impact these initiatives produce on urban archaeology. During this long period of Spanish recent history, cultural heritage -understood as an important development tool, especially when related to cultural tourism- has succeeded in channeling resources for developing the historical research projects, both documental and archaeological, that the Spanish monumental urban ensembles were requiring. In this context, the case of the city of Madrid is a clear example of the significant development that urban Historical Archaeology has experienced in Spain over the last thirty years, especially when dealing with the study of the Middle Ages (8th to 15th centuries) and the Modern Age (16th to 18th centuries). Given the number of interventions and the important results obtained by many of them, Madrid urban archaeology is an extraordinary example of the consequences of implementing new management models, changing criteria and operating procedures, and also, of course, of the conflicts and debates raised regarding heritage, as well as the importance these interventions have implied, which is the main aim of this work.

Autonomous classification models in ubiquitous environments

Stream-mining approach is defined as a set of cutting-edge techniques designed to process streams of data in real time, in order to extract knowledge. In the particular case of classification, stream-mining has to adapt its behaviour to the volatile underlying data distributions, what has been called concept drift. Moreover, it is important to note that concept drift may lead to situations where predictive models become invalid and have therefore to be updated to represent the actual concepts that data poses. In this context, there is a specific type of concept drift, known as recurrent concept drift, where the concepts represented by data have already appeared in the past. In those cases the learning process could be saved or at least minimized by applying a previously trained model. This could be extremely useful in ubiquitous environments that are characterized by the existence of resource constrained devices. To deal with the aforementioned scenario, meta-models can be used in the process of enhancing the drift detection mechanisms used by data stream algorithms, by representing and predicting when the change will occur. There are some real-world situations where a concept reappears, as in the case of intrusion detection systems (IDS), where the same incidents or an adaptation of them usually reappear over time. In these environments the early prediction of drift by means of a better knowledge of past models can help to anticipate to the change, thus improving efficiency of the model regarding the training instances needed. By means of using meta-models as a recurrent drift detection mechanism, the ability to share concepts representations among different data mining processes is open. That kind of exchanges could improve the accuracy of the resultant local model as such model may benefit from patterns similar to the local concept that were observed in other scenarios, but not yet locally. This would also improve the efficiency of training instances used during the classification process, as long as the exchange of models would aid in the application of already trained recurrent models, that have been previously seen by any of the collaborative devices. Which it is to say that the scope of recurrence detection and representation is broaden. In fact the detection, representation and exchange of concept drift patterns would be extremely useful for the law enforcement activities fighting against cyber crime. Being the information exchange one of the main pillars of cooperation, national units would benefit from the experience and knowledge gained by third parties. Moreover, in the specific scope of critical infrastructures protection it is crucial to count with information exchange mechanisms, both from a strategical and technical scope. The exchange of concept drift detection schemes in cyber security environments would aid in the process of preventing, detecting and effectively responding to threads in cyber space. Furthermore, as a complement of meta-models, a mechanism to assess the similarity between classification models is also needed when dealing with recurrent concepts. In this context, when reusing a previously trained model a rough comparison between concepts is usually made, applying boolean logic. The introduction of fuzzy logic comparisons between models could lead to a better efficient reuse of previously seen concepts, by applying not just equal models, but also similar ones. This work faces the aforementioned open issues by means of: the MMPRec system, that integrates a meta-model mechanism and a fuzzy similarity function; a collaborative environment to share meta-models between different devices; a recurrent drift generator that allows to test the usefulness of recurrent drift systems, as it is the case of MMPRec. Moreover, this thesis presents an experimental validation of the proposed contributions using synthetic and real datasets.