Economic efficiency of members of protected designations of origin: sharing reputation indicators in the experience goods of wine and cheese

The aim of this paper is to analyse the economic efficiency of members of protected designations of origin (PDO). For the first time we analyse the value of PDO labels from the point of view of economic efficiency. The central hypothesis is that a PDO has a positive impact on the economic efficiency of its member companies and that this is because a PDO label is a collective reputation indicator that foments efficient investment in quality in terms of member returns. The methodology applied to test this hypothesis is based on data envelopment analysis to estimate economic efficiency, and econometric models to explain company efficiency through both the PDO label, as an indicator of collective reputation, and the characteristics of the company. The results obtained in the experience goods of wine and cheese in Spain show that PDO labels have a positive impact on economic efficiency. Additionally, the age and size of the company have a positive effect while the wage level of the company has a different influence on efficiency depending on the sector considered. Overall, the results reveal the importance of PDOs in industries in which the signal of reputation is not only reliant on the individual brands.

Indigenous Intellectual Property: A Handbook of Contemporary Research

Taking an interdisciplinary approach unmatched by any other book on this topic, this thoughtful Handbook considers the international struggle to provide for proper and just protection of Indigenous intellectual property (IP). In light of the United Nations Declaration on the Rights of Indigenous Peoples 2007, expert contributors assess the legal and policy controversies over Indigenous knowledge in the fields of international law, copyright law, trademark law, patent law, trade secrets law, and cultural heritage. The overarching discussion examines national developments in Indigenous IP in the United States, Canada, South Africa, the European Union, Australia, New Zealand, and Indonesia. The Handbook provides a comprehensive overview of the historical origins of conflict over Indigenous knowledge, and examines new challenges to Indigenous IP from emerging developments in information technology, biotechnology, and climate change. Practitioners and scholars in the field of IP will learn a great deal from this Handbook about the issues and challenges that surround just protection of a variety of forms of IP for Indigenous communities. Preface The Legacy of David Unaipon Matthew Rimmer Introduction: Mapping Indigenous Intellectual Property Matthew Rimmer PART I INTERNATIONAL LAW 1. The United Nations Declaration on the Rights of Indigenous Peoples: A Human Rights Framework for Indigenous Intellectual Property Mauro Barelli 2. The WTO, The TRIPS Agreement and Traditional Knowledge Tania Voon 3. The World Intellectual Property Organization and Traditional Knowledge Sara Bannerman 4. The World Indigenous Network: Rio+20, Intellectual Property, Indigenous Knowledge, and Sustainable Development Matthew Rimmer PART II COPYRIGHT LAW AND RELATED RIGHTS 5. Government Man, Government Painting? David Malangi and the 1966 One-Dollar Note Stephen Gray 6. What Wandjuk Wanted Martin Hardie 7. Avatar Dreaming: Indigenous Cultural Protocols and Making Films Using Indigenous Content Terri Janke 8. The Australian Resale Royalty for Visual Artists: Indigenous Art and Social Justice Robert Dearn and Matthew Rimmer PART III TRADE MARK LAW AND RELATED RIGHTS 9. Indigenous Cultural Expression and Registered Designs Maree Sainsbury 10. The Indian Arts and Crafts Act: The Limits of Trademark Analogies Rebecca Tushnet 11. Protection of Traditional Cultural Expressions within the New Zealand Intellectual Property Framework: A Case Study of the Ka Mate Haka Sarah Rosanowski 12 Geographical Indications and Indigenous Intellectual Property William van Caenegem PART IV PATENT LAW AND RELATED RIGHTS 13. Pressuring ‘Suspect Orthodoxy’: Traditional Knowledge and the Patent System Chidi Oguamanam, 14. The Nagoya Protocol: Unfinished Business Remains Unfinished Achmad Gusman Siswandi 15. Legislating on Biopiracy in Europe: Too Little, too Late? Angela Daly 16. Intellectual Property, Indigenous Knowledge, and Climate Change Matthew Rimmer PART V PRIVACY LAW AND IDENTITY RIGHTS 17. Confidential Information and Anthropology: Indigenous Knowledge and the Digital Economy Sarah Holcombe 18. Indigenous Cultural Heritage in Australia: The Control of Living Heritages Judith Bannister 19. Dignity, Trust and Identity: Private Spheres and Indigenous Intellectual Property Bruce Baer Arnold 20. Racial Discrimination Laws as a Means of Protecting Collective Reputation and Identity David Rolph PART VI INDIGENOUS INTELLECTUAL PROPERTY: REGIONAL PERSPECTIVES 21. Diluted Control: A Critical Analysis of the WAI262 Report on Maori Traditional Knowledge and Culture Fleur Adcock 22. Traditional Knowledge Governance Challenges in Canada Jeremy de Beer and Daniel Dylan 23. Intellectual Property protection of Traditional Knowledge and Access to Knowledge in South Africa Caroline Ncube 24. Traditional Knowledge Sovereignty: The Fundamental Role of Customary Law in Protection of Traditional Knowledge Brendan Tobin Index

Valor de marca colectiva: aproximación desde el enfoque de la eficiencia

El objetivo del trabajo consiste en analizar la eficiencia de las empresas que integran una marca colectiva en una industria productora de bienes de experiencia. El supuesto básico es que la marca colectiva tiene un impacto positivo en la eficiencia de las empresas acogidas a la misma, el cual viene explicado porque la reputación colectiva fomenta una inversión eficiente en calidad. Sin embargo, la marca colectiva también puede tener un efecto opuesto sobre los incentivos de una empresa a una inversión en calidad ya que dicha marca puede crear un incentivo a “free ride”. Nuestra propuesta defiende que la interacción entre estos factores opuestos, reputación colectiva y “free ride”, viene moderada por las características de la marca colectiva y de la propia empresa. La metodología aplicada en el contraste de estas hipótesis se apoya en el Análisis Envolvente de Datos para estimar la eficiencia, así como en modelos econométricos para explicar la eficiencia empresarial mediante características de la marca colectiva y de la empresa. Los resultados obtenidos en el ámbito de las bodegas españolas evidencian que las marcas colectivas tienen un impacto positivo sobre la eficiencia, el cual viene moderado por el tamaño de la marca colectiva generando una relación curvilínea en forma de U invertida. Adicionalmente, el volumen de producción de la marca colectiva y el tamaño de las bodegas ejercen un efecto moderador en el impacto del tamaño de la marca colectiva sobre la eficiencia. En general, los resultados ponen de manifiesto la importancia de las marcas colectivas cuando se investigan industrias donde la calidad no es solamente señalizada por una marca típica individual.

Rentabilidad de las empresas vinculadas a las marcas colectivas en el sector vinícola

El objetivo del trabajo consiste en analizar la rentabilidad de las empresas que integran una marca colectiva en el sector vinícola español. El supuesto básico es que la marca colectiva puede explicar la rentabilidad de las bodegas, porque la reputación colectiva es una señal de calidad que reduce las percepciones de riesgo del consumidor. Los resultados obtenidos evidencian que sólo algunas marcas colectivas tienen un efecto positivo en la rentabilidad de las bodegas en relación con las no acogidas a dichas marcas colectivas. Asimismo, la rentabilidad viene asociada positivamente a la diversificación de la bodega en dos o más marcas colectivas.

Da casta ao terroir

Pela importância atual – e crescente – que o vinho tem na economia portuguesa, pela margem existente para a apresentação de temas de reflexão que acrescentem valor ao posicionamento do setor, pela experiência pessoal e paixão pela área, decidi elaborar a minha dissertação numa temática enquadrável no setor do vinho, em particular no vinho Alvarinho proveniente do terroir que representa a Denominação de Origem Vinho Verde Sub-região de Monção e Melgaço. A estrutura deste estudo assenta em duas dimensões: a primeira, numa perspetiva local, assente na recente decisão de alargar a Denominação Origem Vinho Verde Alvarinho a todas as sub-regiões que integram a Região dos Vinhos Verdes, com efeitos em 2021. Pelo que se procurará mostrar a importância da relação desta casta com o seu terroir de origem e, perante esta interligação, qual o fator mais importante a utilizar na comunicação do vinho. A segunda prende-se com a dimensão internacional que se pretende para o Alvarinho no mercado dos grandes vinhos brancos mundiais, onde encontramos castas brancas de renome como a Chardonnay e a Riesling, face a esta exposição e à crescente aposta na casta a nível mundial, como agir perante a potencial ameaça que representa a entrada dos países do “Novo Mundo”. Posto isto, é neste contexto que se coloca a questão que está na génese desta dissertação: de que forma o terroir contribui como fator de diferenciação e de vantagem competitiva do Alvarinho produzido na Denominação de Origem Vinho Verde Sub-região Monção e Melgaço no mercado dos grandes vinhos brancos mundiais? Cuja resposta poderá em grande parte estar, no meu entendimento, na análise de um caso de sucesso, que nesta dissertação é representada pelo trabalho realizado em torno do Rieseling produzido no Vale de Mosel e que contribuiu para que este tivesse conquistado a sua reputação.

Cultural selection and its influence on perceptions of reputation within organisations

The capacity to identify, interpret, and prioritise environmental issues is critical in the management of corporate reputation. In spite of the significance of these abilities for corporate reputation management, there has been little effort to document and describe internal organizational influences on these capacities. Contrary to this state of affairs in the discipline of public relations, a long history of ethnographic research in cultural anthropology documents how sets of shared environmental perceptions can influence and moderate environmental factors in cultural populations (see for example, Durham, 1991 ). This study explores how cultural “frames of reference” derived from shared values and assumptions among organizational members influence organizational perceptions, and consequently, organizational actions. Specifically, this study explores how a central attribute of organizational culture--the property of cultural selection-- influences perceptions of organizational reputation held by organizational members. Perceptions of reputation among organizational members are obvious drivers to both the nature of and rationale for organizational communication strategies and responses. These perceptions are the result of collective processes that synthesise (with varying degrees of consensus) member conceptualisations, interpretations, and representations of the environmental realities in which their organization operate. To explore how cultural selection influences member perceptions of organizational reputation, this study employs ethnographic research including 20 depth interviews and six months of organizational observation in the focal organization. We argue that while external indicators of organizational reputation are acknowledged by members as significant, the internal action of cultural selection is a far stronger influence on organizational action.

Overcoming reputation and proof-of-work systems in botnets

Reputation and proof-of-work systems have been outlined as methods bot masters will soon use to defend their peer-to-peer botnets. These techniques are designed to prevent sybil attacks, such as those that led to the downfall of the Storm botnet. To evaluate the effectiveness of these techniques, a botnet that employed these techniques was simulated, and the amount of resources required to stage a successful sybil attack against it measured. While the proof-of-work system was found to increase the resources required for a successful sybil attack, the reputation system was found to lower the amount of resources required to disable the botnet.

Large scale participatory acoustic sensor data analysis : tools and reputation models to enhance effectiveness

Acoustic sensors play an important role in augmenting the traditional biodiversity monitoring activities carried out by ecologists and conservation biologists. With this ability however comes the burden of analysing large volumes of complex acoustic data. Given the complexity of acoustic sensor data, fully automated analysis for a wide range of species is still a significant challenge. This research investigates the use of citizen scientists to analyse large volumes of environmental acoustic data in order to identify bird species. Specifically, it investigates ways in which the efficiency of a user can be improved through the use of species identification tools and the use of reputation models to predict the accuracy of users with unidentified skill levels. Initial experimental results are reported.

Employee perceptions of reputation : an ethnographic study

The ability of organizational members to identify and analyse stakeholder opinion is critical to the management of corporate reputation. In spite of the significance of these abilities to corporate reputation management, there has been little effort to document and describe internal organizational influences on such capacities. This ethnographic study conducted in Red Cross Queensland explores how cultural knowledge structures derived from shared values and assumptions among organizational members influence their conceptualisations of organizational reputation. Specifically, this study explores how a central attribute of organizational culture – the property of cultural selection – influences perceptions of organizational reputation held by organizational members. We argue that these perceptions are the result of collective processes that synthesise (with varying degrees of consensus) member conceptualisations, interpretations, and representations of environmental realities in which their organization operates. Findings and implications for organizational action suggest that while external indicators of organizational reputation are acknowledged by members as significant, the internal influence of organizational culture is a far stronger influence on organizational action.

An accurate rating aggregation method for generating item reputation

Many websites presently provide the facility for users to rate items quality based on user opinion. These ratings are used later to produce item reputation scores. The majority of websites apply the mean method to aggregate user ratings. This method is very simple and is not considered as an accurate aggregator. Many methods have been proposed to make aggregators produce more accurate reputation scores. In the majority of proposed methods the authors use extra information about the rating providers or about the context (e.g. time) in which the rating was given. However, this information is not available all the time. In such cases these methods produce reputation scores using the mean method or other alternative simple methods. In this paper, we propose a novel reputation model that generates more accurate item reputation scores based on collected ratings only. Our proposed model embeds statistical data, previously disregarded, of a given rating dataset in order to enhance the accuracy of the generated reputation scores. In more detail, we use the Beta distribution to produce weights for ratings and aggregate ratings using the weighted mean method. Experiments show that the proposed model exhibits performance superior to that of current state-of-the-art models.

Fuzzy Web Knowledge Aggregation, Representation, and Reasoning for Online Privacy and Reputation Management

A social Semantic Web empowers its users to have access to collective Web knowledge in a simple manner, and for that reason, controlling online privacy and reputation becomes increasingly important, and must be taken seriously. This chapter presents Fuzzy Cognitive Maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. With this in mind, a conceptual framework for Web knowledge aggregation, representation, and reasoning is introduced along with a use case, in which the importance of investigative searching for online privacy and reputation is highlighted. Thereby it is demonstrated how a user can establish a positive online presence.

How Firms Make Friends: Communities in Private-Collective Innovation

When firms contribute to open source projects, they in fact invest into public goods which may be used by everyone, even by their competitors. This seemingly paradoxical behavior can be explained by the model of private-collective innovation where private investors participate in collective action. Previous literature has shown that companies benefit through the production process providing them with unique incentives such as learning and reputation effects. By contributing to open source projects firms are able to build a network of external individuals and organizations participating in the creation and development of the software. As will be shown in this doctoral dissertation firm-sponsored communities involve the formation of interorganizational relationships which eventually may lead to a source of sustained competitive advantage. However, managing a largely independent open source community is a challenging balancing act between exertion of control to appropriate value creation, and openness in order to gain and preserve credibility and motivate external contributions. Therefore, this dissertation consisting of an introductory chapter and three separate research papers analyzes characteristics of firm-driven open source communities, finds reasons why and mechanisms by which companies facilitate the creation of such networks, and shows how firms can benefit most from their communities.

Trust-ware: A Methodology to Analyze, Design, and Secure Trust and Reputation Systems

Entendemos por inteligencia colectiva una forma de inteligencia que surge de la colaboración y la participación de varios individuos o, siendo más estrictos, varias entidades. En base a esta sencilla definición podemos observar que este concepto es campo de estudio de las más diversas disciplinas como pueden ser la sociología, las tecnologías de la información o la biología, atendiendo cada una de ellas a un tipo de entidades diferentes: seres humanos, elementos de computación o animales. Como elemento común podríamos indicar que la inteligencia colectiva ha tenido como objetivo el ser capaz de fomentar una inteligencia de grupo que supere a la inteligencia individual de las entidades que lo forman a través de mecanismos de coordinación, cooperación, competencia, integración, diferenciación, etc. Sin embargo, aunque históricamente la inteligencia colectiva se ha podido desarrollar de forma paralela e independiente en las distintas disciplinas que la tratan, en la actualidad, los avances en las tecnologías de la información han provocado que esto ya no sea suficiente. Hoy en día seres humanos y máquinas a través de todo tipo de redes de comunicación e interfaces, conviven en un entorno en el que la inteligencia colectiva ha cobrado una nueva dimensión: ya no sólo puede intentar obtener un comportamiento superior al de sus entidades constituyentes sino que ahora, además, estas inteligencias individuales son completamente diferentes unas de otras y aparece por lo tanto el doble reto de ser capaces de gestionar esta gran heterogeneidad y al mismo tiempo ser capaces de obtener comportamientos aún más inteligentes gracias a las sinergias que los distintos tipos de inteligencias pueden generar. Dentro de las áreas de trabajo de la inteligencia colectiva existen varios campos abiertos en los que siempre se intenta obtener unas prestaciones superiores a las de los individuos. Por ejemplo: consciencia colectiva, memoria colectiva o sabiduría colectiva. Entre todos estos campos nosotros nos centraremos en uno que tiene presencia en la práctica totalidad de posibles comportamientos inteligentes: la toma de decisiones. El campo de estudio de la toma de decisiones es realmente amplio y dentro del mismo la evolución ha sido completamente paralela a la que citábamos anteriormente en referencia a la inteligencia colectiva. En primer lugar se centró en el individuo como entidad decisoria para posteriormente desarrollarse desde un punto de vista social, institucional, etc. La primera fase dentro del estudio de la toma de decisiones se basó en la utilización de paradigmas muy sencillos: análisis de ventajas e inconvenientes, priorización basada en la maximización de algún parámetro del resultado, capacidad para satisfacer los requisitos de forma mínima por parte de las alternativas, consultas a expertos o entidades autorizadas o incluso el azar. Sin embargo, al igual que el paso del estudio del individuo al grupo supone una nueva dimensión dentro la inteligencia colectiva la toma de decisiones colectiva supone un nuevo reto en todas las disciplinas relacionadas. Además, dentro de la decisión colectiva aparecen dos nuevos frentes: los sistemas de decisión centralizados y descentralizados. En el presente proyecto de tesis nos centraremos en este segundo, que es el que supone una mayor atractivo tanto por las posibilidades de generar nuevo conocimiento y trabajar con problemas abiertos actualmente así como en lo que respecta a la aplicabilidad de los resultados que puedan obtenerse. Ya por último, dentro del campo de los sistemas de decisión descentralizados existen varios mecanismos fundamentales que dan lugar a distintas aproximaciones a la problemática propia de este campo. Por ejemplo el liderazgo, la imitación, la prescripción o el miedo. Nosotros nos centraremos en uno de los más multidisciplinares y con mayor capacidad de aplicación en todo tipo de disciplinas y que, históricamente, ha demostrado que puede dar lugar a prestaciones muy superiores a otros tipos de mecanismos de decisión descentralizados: la confianza y la reputación. Resumidamente podríamos indicar que confianza es la creencia por parte de una entidad que otra va a realizar una determinada actividad de una forma concreta. En principio es algo subjetivo, ya que la confianza de dos entidades diferentes sobre una tercera no tiene porqué ser la misma. Por otro lado, la reputación es la idea colectiva (o evaluación social) que distintas entidades de un sistema tiene sobre otra entidad del mismo en lo que respecta a un determinado criterio. Es por tanto una información de carácter colectivo pero única dentro de un sistema, no asociada a cada una de las entidades del sistema sino por igual a todas ellas. En estas dos sencillas definiciones se basan la inmensa mayoría de sistemas colectivos. De hecho muchas disertaciones indican que ningún tipo de organización podría ser viable de no ser por la existencia y la utilización de los conceptos de confianza y reputación. A partir de ahora, a todo sistema que utilice de una u otra forma estos conceptos lo denominaremos como sistema de confianza y reputación (o TRS, Trust and Reputation System). Sin embargo, aunque los TRS son uno de los aspectos de nuestras vidas más cotidianos y con un mayor campo de aplicación, el conocimiento que existe actualmente sobre ellos no podría ser más disperso. Existen un gran número de trabajos científicos en todo tipo de áreas de conocimiento: filosofía, psicología, sociología, economía, política, tecnologías de la información, etc. Pero el principal problema es que no existe una visión completa de la confianza y reputación en su sentido más amplio. Cada disciplina focaliza sus estudios en unos aspectos u otros dentro de los TRS, pero ninguna de ellas trata de explotar el conocimiento generado en el resto para mejorar sus prestaciones en su campo de aplicación concreto. Aspectos muy detallados en algunas áreas de conocimiento son completamente obviados por otras, o incluso aspectos tratados por distintas disciplinas, al ser estudiados desde distintos puntos de vista arrojan resultados complementarios que, sin embargo, no son aprovechados fuera de dichas áreas de conocimiento. Esto nos lleva a una dispersión de conocimiento muy elevada y a una falta de reutilización de metodologías, políticas de actuación y técnicas de una disciplina a otra. Debido su vital importancia, esta alta dispersión de conocimiento se trata de uno de los principales problemas que se pretenden resolver con el presente trabajo de tesis. Por otro lado, cuando se trabaja con TRS, todos los aspectos relacionados con la seguridad están muy presentes ya que muy este es un tema vital dentro del campo de la toma de decisiones. Además también es habitual que los TRS se utilicen para desempeñar responsabilidades que aportan algún tipo de funcionalidad relacionada con el mundo de la seguridad. Por último no podemos olvidar que el acto de confiar está indefectiblemente unido al de delegar una determinada responsabilidad, y que al tratar estos conceptos siempre aparece la idea de riesgo, riesgo de que las expectativas generadas por el acto de la delegación no se cumplan o se cumplan de forma diferente. Podemos ver por lo tanto que cualquier sistema que utiliza la confianza para mejorar o posibilitar su funcionamiento, por su propia naturaleza, es especialmente vulnerable si las premisas en las que se basa son atacadas. En este sentido podemos comprobar (tal y como analizaremos en más detalle a lo largo del presente documento) que las aproximaciones que realizan las distintas disciplinas que tratan la violación de los sistemas de confianza es de lo más variado. únicamente dentro del área de las tecnologías de la información se ha intentado utilizar alguno de los enfoques de otras disciplinas de cara a afrontar problemas relacionados con la seguridad de TRS. Sin embargo se trata de una aproximación incompleta y, normalmente, realizada para cumplir requisitos de aplicaciones concretas y no con la idea de afianzar una base de conocimiento más general y reutilizable en otros entornos. Con todo esto en cuenta, podemos resumir contribuciones del presente trabajo de tesis en las siguientes. • La realización de un completo análisis del estado del arte dentro del mundo de la confianza y la reputación que nos permite comparar las ventajas e inconvenientes de las diferentes aproximación que se realizan a estos conceptos en distintas áreas de conocimiento. • La definición de una arquitectura de referencia para TRS que contempla todas las entidades y procesos que intervienen en este tipo de sistemas. • La definición de un marco de referencia para analizar la seguridad de TRS. Esto implica tanto identificar los principales activos de un TRS en lo que respecta a la seguridad, así como el crear una tipología de posibles ataques y contramedidas en base a dichos activos. • La propuesta de una metodología para el análisis, el diseño, el aseguramiento y el despliegue de un TRS en entornos reales. Adicionalmente se exponen los principales tipos de aplicaciones que pueden obtenerse de los TRS y los medios para maximizar sus prestaciones en cada una de ellas. • La generación de un software que permite simular cualquier tipo de TRS en base a la arquitectura propuesta previamente. Esto permite evaluar las prestaciones de un TRS bajo una determinada configuración en un entorno controlado previamente a su despliegue en un entorno real. Igualmente es de gran utilidad para evaluar la resistencia a distintos tipos de ataques o mal-funcionamientos del sistema. Además de las contribuciones realizadas directamente en el campo de los TRS, hemos realizado aportaciones originales a distintas áreas de conocimiento gracias a la aplicación de las metodologías de análisis y diseño citadas con anterioridad. • Detección de anomalías térmicas en Data Centers. Hemos implementado con éxito un sistema de deteción de anomalías térmicas basado en un TRS. Comparamos la detección de prestaciones de algoritmos de tipo Self-Organized Maps (SOM) y Growing Neural Gas (GNG). Mostramos como SOM ofrece mejores resultados para anomalías en los sistemas de refrigeración de la sala mientras que GNG es una opción más adecuada debido a sus tasas de detección y aislamiento para casos de anomalías provocadas por una carga de trabajo excesiva. • Mejora de las prestaciones de recolección de un sistema basado en swarm computing y odometría social. Gracias a la implementación de un TRS conseguimos mejorar las capacidades de coordinación de una red de robots autónomos distribuidos. La principal contribución reside en el análisis y la validación de las mejoras increméntales que pueden conseguirse con la utilización apropiada de la información existente en el sistema y que puede ser relevante desde el punto de vista de un TRS, y con la implementación de algoritmos de cálculo de confianza basados en dicha información. • Mejora de la seguridad de Wireless Mesh Networks contra ataques contra la integridad, la confidencialidad o la disponibilidad de los datos y / o comunicaciones soportadas por dichas redes. • Mejora de la seguridad de Wireless Sensor Networks contra ataques avanzamos, como insider attacks, ataques desconocidos, etc. Gracias a las metodologías presentadas implementamos contramedidas contra este tipo de ataques en entornos complejos. En base a los experimentos realizados, hemos demostrado que nuestra aproximación es capaz de detectar y confinar varios tipos de ataques que afectan a los protocoles esenciales de la red. La propuesta ofrece unas velocidades de detección muy altas así como demuestra que la inclusión de estos mecanismos de actuación temprana incrementa significativamente el esfuerzo que un atacante tiene que introducir para comprometer la red. Finalmente podríamos concluir que el presente trabajo de tesis supone la generación de un conocimiento útil y aplicable a entornos reales, que nos permite la maximización de las prestaciones resultantes de la utilización de TRS en cualquier tipo de campo de aplicación. De esta forma cubrimos la principal carencia existente actualmente en este campo, que es la falta de una base de conocimiento común y agregada y la inexistencia de una metodología para el desarrollo de TRS que nos permita analizar, diseñar, asegurar y desplegar TRS de una forma sistemática y no artesanal y ad-hoc como se hace en la actualidad. ABSTRACT By collective intelligence we understand a form of intelligence that emerges from the collaboration and competition of many individuals, or strictly speaking, many entities. Based on this simple definition, we can see how this concept is the field of study of a wide range of disciplines, such as sociology, information science or biology, each of them focused in different kinds of entities: human beings, computational resources, or animals. As a common factor, we can point that collective intelligence has always had the goal of being able of promoting a group intelligence that overcomes the individual intelligence of the basic entities that constitute it. This can be accomplished through different mechanisms such as coordination, cooperation, competence, integration, differentiation, etc. Collective intelligence has historically been developed in a parallel and independent way among the different disciplines that deal with it. However, this is not enough anymore due to the advances in information technologies. Nowadays, human beings and machines coexist in environments where collective intelligence has taken a new dimension: we yet have to achieve a better collective behavior than the individual one, but now we also have to deal with completely different kinds of individual intelligences. Therefore, we have a double goal: being able to deal with this heterogeneity and being able to get even more intelligent behaviors thanks to the synergies that the different kinds of intelligence can generate. Within the areas of collective intelligence there are several open topics where they always try to get better performances from groups than from the individuals. For example: collective consciousness, collective memory, or collective wisdom. Among all these topics we will focus on collective decision making, that has influence in most of the collective intelligent behaviors. The field of study of decision making is really wide, and its evolution has been completely parallel to the aforementioned collective intelligence. Firstly, it was focused on the individual as the main decision-making entity, but later it became involved in studying social and institutional groups as basic decision-making entities. The first studies within the decision-making discipline were based on simple paradigms, such as pros and cons analysis, criteria prioritization, fulfillment, following orders, or even chance. However, in the same way that studying the community instead of the individual meant a paradigm shift within collective intelligence, collective decision-making means a new challenge for all the related disciplines. Besides, two new main topics come up when dealing with collective decision-making: centralized and decentralized decision-making systems. In this thesis project we focus in the second one, because it is the most interesting based on the opportunities to generate new knowledge and deal with open issues in this area, as well as these results can be put into practice in a wider set of real-life environments. Finally, within the decentralized collective decision-making systems discipline, there are several basic mechanisms that lead to different approaches to the specific problems of this field, for example: leadership, imitation, prescription, or fear. We will focus on trust and reputation. They are one of the most multidisciplinary concepts and with more potential for applying them in every kind of environments. Besides, they have historically shown that they can generate better performance than other decentralized decision-making mechanisms. Shortly, we say trust is the belief of one entity that the outcome of other entities’ actions is going to be in a specific way. It is a subjective concept because the trust of two different entities in another one does not have to be the same. Reputation is the collective idea (or social evaluation) that a group of entities within a system have about another entity based on a specific criterion. Thus, it is a collective concept in its origin. It is important to say that the behavior of most of the collective systems are based on these two simple definitions. In fact, a lot of articles and essays describe how any organization would not be viable if the ideas of trust and reputation did not exist. From now on, we call Trust an Reputation System (TRS) to any kind of system that uses these concepts. Even though TRSs are one of the most common everyday aspects in our lives, the existing knowledge about them could not be more dispersed. There are thousands of scientific works in every field of study related to trust and reputation: philosophy, psychology, sociology, economics, politics, information sciences, etc. But the main issue is that a comprehensive vision of trust and reputation for all these disciplines does not exist. Every discipline focuses its studies on a specific set of topics but none of them tries to take advantage of the knowledge generated in the other disciplines to improve its behavior or performance. Detailed topics in some fields are completely obviated in others, and even though the study of some topics within several disciplines produces complementary results, these results are not used outside the discipline where they were generated. This leads us to a very high knowledge dispersion and to a lack in the reuse of methodologies, policies and techniques among disciplines. Due to its great importance, this high dispersion of trust and reputation knowledge is one of the main problems this thesis contributes to solve. When we work with TRSs, all the aspects related to security are a constant since it is a vital aspect within the decision-making systems. Besides, TRS are often used to perform some responsibilities related to security. Finally, we cannot forget that the act of trusting is invariably attached to the act of delegating a specific responsibility and, when we deal with these concepts, the idea of risk is always present. This refers to the risk of generated expectations not being accomplished or being accomplished in a different way we anticipated. Thus, we can see that any system using trust to improve or enable its behavior, because of its own nature, is especially vulnerable if the premises it is based on are attacked. Related to this topic, we can see that the approaches of the different disciplines that study attacks of trust and reputation are very diverse. Some attempts of using approaches of other disciplines have been made within the information science area of knowledge, but these approaches are usually incomplete, not systematic and oriented to achieve specific requirements of specific applications. They never try to consolidate a common base of knowledge that could be reusable in other context. Based on all these ideas, this work makes the following direct contributions to the field of TRS: • The compilation of the most relevant existing knowledge related to trust and reputation management systems focusing on their advantages and disadvantages. • We define a generic architecture for TRS, identifying the main entities and processes involved. • We define a generic security framework for TRS. We identify the main security assets and propose a complete taxonomy of attacks for TRS. • We propose and validate a methodology to analyze, design, secure and deploy TRS in real-life environments. Additionally we identify the principal kind of applications we can implement with TRS and how TRS can provide a specific functionality. • We develop a software component to validate and optimize the behavior of a TRS in order to achieve a specific functionality or performance. In addition to the contributions made directly to the field of the TRS, we have made original contributions to different areas of knowledge thanks to the application of the analysis, design and security methodologies previously presented: • Detection of thermal anomalies in Data Centers. Thanks to the application of the TRS analysis and design methodologies, we successfully implemented a thermal anomaly detection system based on a TRS.We compare the detection performance of Self-Organized- Maps and Growing Neural Gas algorithms. We show how SOM provides better results for Computer Room Air Conditioning anomaly detection, yielding detection rates of 100%, in training data with malfunctioning sensors. We also show that GNG yields better detection and isolation rates for workload anomaly detection, reducing the false positive rate when compared to SOM. • Improving the performance of a harvesting system based on swarm computing and social odometry. Through the implementation of a TRS, we achieved to improve the ability of coordinating a distributed network of autonomous robots. The main contribution lies in the analysis and validation of the incremental improvements that can be achieved with proper use information that exist in the system and that are relevant for the TRS, and the implementation of the appropriated trust algorithms based on such information. • Improving Wireless Mesh Networks security against attacks against the integrity, confidentiality or availability of data and communications supported by these networks. Thanks to the implementation of a TRS we improved the detection time rate against these kind of attacks and we limited their potential impact over the system. • We improved the security of Wireless Sensor Networks against advanced attacks, such as insider attacks, unknown attacks, etc. Thanks to the TRS analysis and design methodologies previously described, we implemented countermeasures against such attacks in a complex environment. In our experiments we have demonstrated that our system is capable of detecting and confining various attacks that affect the core network protocols. We have also demonstrated that our approach is capable of rapid attack detection. Also, it has been proven that the inclusion of the proposed detection mechanisms significantly increases the effort the attacker has to introduce in order to compromise the network. Finally we can conclude that, to all intents and purposes, this thesis offers a useful and applicable knowledge in real-life environments that allows us to maximize the performance of any system based on a TRS. Thus, we deal with the main deficiency of this discipline: the lack of a common and complete base of knowledge and the lack of a methodology for the development of TRS that allow us to analyze, design, secure and deploy TRS in a systematic way.