Testbed Evaluation of Sensor Node Overlay Multicast

The Sensor Node Overlay Multicast (SNOMC) protocol supports reliable, time-efficient and energy-efficient dissemination of data from one sender node to multiple receivers as it is needed for configuration, code update, and management operations in wireless sensor networks. SNOMC supports end-to-end reliability using negative acknowledgements. The mechanism is simple and easy to implement and can significantly reduce the number of transmissions. SNOMC supports three different caching strategies namely caching on each intermediate node, caching on branching nodes, or caching on the sender node only. SNOMC was evaluated in our in-house real-world testbed and compared to a number of common data dissemination protocols. It outperforms the selected protocols in terms of transmission time, number of transmitted packets, and energy-consumption.

Real-World Evaluation of Sensor Context-aware Adaptive Duty-cycled Opportunistic Routing

Energy is of primary concern in wireless sensor networks (WSNs). Low power transmission makes the wireless links unreliable, which leads to frequent topology changes. Resulting packet retransmissions aggravate the energy consumption. Beaconless routing approaches, such as opportunistic routing (OR) choose packet forwarders after data transmissions, and are promising to support dynamic features of WSNs. This paper proposes SCAD - Sensor Context-aware Adaptive Duty-cycled beaconless OR for WSNs. SCAD is a cross-layer routing solution and it brings the concept of beaconless OR into WSNs. SCAD selects packet forwarders based on multiple types of network contexts. To achieve a balance between performance and energy efficiency, SCAD adapts duty-cycles of sensors based on real-time traffic loads and energy drain rates. We implemented SCAD in TinyOS running on top of Tmote Sky sensor motes. Real-world evaluations show that SCAD outperforms other protocols in terms of both throughput and network lifetime.

SCAD: Sensor Context-aware Adaptive Duty-cycled Beaconless Opportunistic Routing for WSNs

Low quality of wireless links leads to perpetual transmission failures in lossy wireless environments. To mitigate this problem, opportunistic routing (OR) has been proposed to improve the throughput of wireless multihop ad-hoc networks by taking advantage of the broadcast nature of wireless channels. However, OR can not be directly applied to wireless sensor networks (WSNs) due to some intrinsic design features of WSNs. In this paper, we present a new OR solution for WSNs with suitable adaptations to their characteristics. Our protocol, called SCAD-Sensor Context-aware Adaptive Duty-cycled beaconless opportunistic routing protocol is a cross-layer routing approach and it selects packet forwarders based on multiple sensor context information. To reach a balance between performance and energy-efficiency, SCAD adapts the duty-cycles of sensors according to real-time traffic loads and energy drain rates. We compare SCAD against other protocols through extensive simulations. Evaluation results show that SCAD outperforms other protocols in highly dynamic scenarios.

A low power routing algorithm for localization in IEEE 802.15.4 networks

Many context-aware applications rely on the knowledge of the position of the user and the surrounding objects to provide advanced, personalized and real-time services. In wide-area deployments, a routing protocol is needed to collect the location information from distant nodes. In this paper, we propose a new source-initiated (on demand) routing protocol for location-aware applications in IEEE 802.15.4 wireless sensor networks. This protocol uses a low power MAC layer to maximize the lifetime of the network while maintaining the communication delay to a low value. Its performance is assessed through experimental tests that show a good trade-off between power consumption and time delay in the localization of a mobile device.

Consolidation of a wsn and minimax method to rapidly neutralise intruders in strategic installations

Due to the sensitive international situation caused by still-recent terrorist attacks, there is a common need to protect the safety of large spaces such as government buildings, airports and power stations. To address this problem, developments in several research fields, such as video and cognitive audio, decision support systems, human interface, computer architecture, communications networks and communications security, should be integrated with the goal of achieving advanced security systems capable of checking all of the specified requirements and spanning the gap that presently exists in the current market. This paper describes the implementation of a decision system for crisis management in infrastructural building security. Specifically, it describes the implementation of a decision system in the management of building intrusions. The positions of the unidentified persons are reported with the help of a Wireless Sensor Network (WSN). The goal is to achieve an intelligent system capable of making the best decision in real time in order to quickly neutralise one or more intruders who threaten strategic installations. It is assumed that the intruders’ behaviour is inferred through sequences of sensors’ activations and their fusion. This article presents a general approach to selecting the optimum operation from the available neutralisation strategies based on a Minimax algorithm. The distances among different scenario elements will be used to measure the risk of the scene, so a path planning technique will be integrated in order to attain a good performance. Different actions to be executed over the elements of the scene such as moving a guard, blocking a door or turning on an alarm will be used to neutralise the crisis. This set of actions executed to stop the crisis is known as the neutralisation strategy. Finally, the system has been tested in simulations of real situations, and the results have been evaluated according to the final state of the intruders. In 86.5% of the cases, the system achieved the capture of the intruders, and in 59.25% of the cases, they were intercepted before they reached their objective.

Adaptive cross-device videoconferencing solution for wireless networks based on QoS monitoring

The increase in CPU power and screen quality of todays smartphones as well as the availability of high bandwidth wireless networks has enabled high quality mobile videoconfer- encing never seen before. However, adapting to the variety of devices and network conditions that come as a result is still not a trivial issue. In this paper, we present a multiple participant videoconferencing service that adapts to different kind of devices and access networks while providing an stable communication. By combining network quality detection and the use of a multipoint control unit for video mixing and transcoding, desktop, tablet and mobile clients can participate seamlessly. We also describe the cost in terms of bandwidth and CPU usage of this approach in a variety of scenarios.

Cooperative localization in mobile networks using nonparametric variants of belief propagation

Of the many state-of-the-art methods for cooperative localization in wireless sensor networks (WSN), only very few adapt well to mobile networks. The main problems of the well-known algorithms, based on nonparametric belief propagation (NBP), are the high communication cost and inefficient sampling techniques. Moreover, they either do not use smoothing or just apply it o ine. Therefore, in this article, we propose more flexible and effcient variants of NBP for cooperative localization in mobile networks. In particular, we provide: i) an optional 1-lag smoothing done almost in real-time, ii) a novel low-cost communication protocol based on package approximation and censoring, iii) higher robustness of the standard mixture importance sampling (MIS) technique, and iv) a higher amount of information in the importance densities by using the population Monte Carlo (PMC) approach, or an auxiliary variable. Through extensive simulations, we confirmed that all the proposed techniques outperform the standard NBP method.

PUE attack detection in CWSN using collaboration and learning behavior

Cognitive Wireless Sensor Network (CWSN) is a new paradigm which integrates cognitive features in traditional Wireless Sensor Networks (WSNs) to mitigate important problems such as spectrum occupancy. Security in Cognitive Wireless Sensor Networks is an important problem because these kinds of networks manage critical applications and data. Moreover, the specific constraints of WSN make the problem even more critical. However, effective solutions have not been implemented yet. Among the specific attacks derived from new cognitive features, the one most studied is the Primary User Emulation (PUE) attack. This paper discusses a new approach, based on anomaly behavior detection and collaboration, to detect the PUE attack in CWSN scenarios. A nonparametric CUSUM algorithm, suitable for low resource networks like CWSN, has been used in this work. The algorithm has been tested using a cognitive simulator that brings important results in this area. For example, the result shows that the number of collaborative nodes is the most important parameter in order to improve the PUE attack detection rates. If the 20% of the nodes collaborates, the PUE detection reaches the 98% with less than 1% of false positives.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

A proposal for an Internet of Things-based monitoring system composed by low capability, open source and open hardware devices

The Internet of Things makes use of a huge disparity of technologies at very different levels that help one to the other to accomplish goals that were previously regarded as unthinkable in terms of ubiquity or scalability. If the Internet of Things is expected to interconnect every day devices or appliances and enable communications between them, a broad range of new services, applications and products can be foreseen. For example, monitoring is a process where sensors have widespread use for measuring environmental parameters (temperature, light, chemical agents, etc.) but obtaining readings at the exact physical point they want to be obtained from, or about the exact wanted parameter can be a clumsy, time-consuming task that is not easily adaptable to new requirements. In order to tackle this challenge, a proposal on a system used to monitor any conceivable environment, which additionally is able to monitor the status of its own components and heal some of the most usual issues of a Wireless Sensor Network, is presented here in detail, covering all the layers that give it shape in terms of devices, communications or services.

Contribution towards intelligent service management in wearable and ubiquitous devices

Hoy en día asistimos a un creciente interés por parte de la sociedad hacia el cuidado de la salud. Esta afirmación viene apoyada por dos realidades. Por una parte, el aumento de las prácticas saludables (actividad deportiva, cuidado de la alimentación, etc.). De igual manera, el auge de los dispositivos inteligentes (relojes, móviles o pulseras) capaces de medir distintos parámetros físicos como el pulso cardíaco, el ritmo respiratorio, la distancia recorrida, las calorías consumidas, etc. Combinando ambos factores (interés por el estado de salud y disponibilidad comercial de dispositivos inteligentes) están surgiendo multitud de aplicaciones capaces no solo de controlar el estado actual de salud, también de recomendar al usuario cambios de hábitos que lleven hacia una mejora en su condición física. En este contexto, los llamados dispositivos llevables (weareables) unidos al paradigma de Internet de las cosas (IoT, del inglés Internet of Things) permiten la aparición de nuevos nichos de mercado para aplicaciones que no solo se centran en la mejora de la condición física, ya que van más allá proponiendo soluciones para el cuidado de pacientes enfermos, la vigilancia de niños o ancianos, la defensa y la seguridad, la monitorización de agentes de riesgo (como bomberos o policías) y un largo etcétera de aplicaciones por llegar. El paradigma de IoT se puede desarrollar basándose en las existentes redes de sensores inalámbricos (WSN, del inglés Wireless Sensor Network). La conexión de los ya mencionados dispositivos llevables a estas redes puede facilitar la transición de nuevos usuarios hacia aplicaciones IoT. Pero uno de los problemas intrínsecos a estas redes es su heterogeneidad. En efecto, existen multitud de sistemas operativos, protocolos de comunicación, plataformas de desarrollo, soluciones propietarias, etc. El principal objetivo de esta tesis es realizar aportaciones significativas para solucionar no solo el problema de la heterogeneidad, sino también de dotar de mecanismos de seguridad suficientes para salvaguardad la integridad de los datos intercambiados en este tipo de aplicaciones. Algo de suma importancia ya que los datos médicos y biométricos de los usuarios están protegidos por leyes nacionales y comunitarias. Para lograr dichos objetivos, se comenzó con la realización de un completo estudio del estado del arte en tecnologías relacionadas con el marco de investigación (plataformas y estándares para WSNs e IoT, plataformas de implementación distribuidas, dispositivos llevables y sistemas operativos y lenguajes de programación). Este estudio sirvió para tomar decisiones de diseño fundamentadas en las tres contribuciones principales de esta tesis: un bus de servicios para dispositivos llevables (WDSB, Wearable Device Service Bus) basado en tecnologías ya existentes tales como ESB, WWBAN, WSN e IoT); un protocolo de comunicaciones inter-dominio para dispositivos llevables (WIDP, Wearable Inter-Domain communication Protocol) que integra en una misma solución protocolos capaces de ser implementados en dispositivos de bajas capacidades (como lo son los dispositivos llevables y los que forman parte de WSNs); y finalmente, la tercera contribución relevante es una propuesta de seguridad para WSN basada en la aplicación de dominios de confianza. Aunque las contribuciones aquí recogidas son de aplicación genérica, para su validación se utilizó un escenario concreto de aplicación: una solución para control de parámetros físicos en entornos deportivos, desarrollada dentro del proyecto europeo de investigación “LifeWear”. En este escenario se desplegaron todos los elementos necesarios para validar las contribuciones principales de esta tesis y, además, se realizó una aplicación para dispositivos móviles por parte de uno de los socios del proyecto (lo que contribuyó con una validación externa de la solución). En este escenario se usaron dispositivos llevables tales como un reloj inteligente, un teléfono móvil con sistema operativo Android y un medidor del ritmo cardíaco inalámbrico capaz de obtener distintos parámetros fisiológicos del deportista. Sobre este escenario se realizaron diversas pruebas de validación mediante las cuales se obtuvieron resultados satisfactorios. ABSTRACT Nowadays, society is shifting towards a growing interest and concern on health care. This phenomenon can be acknowledged by two facts: first, the increasing number of people practising some kind of healthy activity (sports, balanced diet, etc.). Secondly, the growing number of commercial wearable smart devices (smartwatches or bands) able to measure physiological parameters such as heart rate, breathing rate, distance or consumed calories. A large number of applications combining both facts are appearing. These applications are not only able to monitor the health status of the user, but also to provide recommendations about routines in order to improve the mentioned health status. In this context, wearable devices merged with the Internet of Things (IoT) paradigm enable the proliferation of new market segments for these health wearablebased applications. Furthermore, these applications can provide solutions for the elderly or baby care, in-hospital or in-home patient monitoring, security and defence fields or an unforeseen number of future applications. The introduced IoT paradigm can be developed with the usage of existing Wireless Sensor Networks (WSNs) by connecting the novel wearable devices to them. In this way, the migration of new users and actors to the IoT environment will be eased. However, a major issue appears in this environment: heterogeneity. In fact, there is a large number of operating systems, hardware platforms, communication and application protocols or programming languages, each of them with unique features. The main objective of this thesis is defining and implementing a solution for the intelligent service management in wearable and ubiquitous devices so as to solve the heterogeneity issues that are presented when dealing with interoperability and interconnectivity of devices and software of different nature. Additionally, a security schema based on trust domains is proposed as a solution to the privacy problems arising when private data (e.g., biomedical parameters or user identification) is broadcasted in a wireless network. The proposal has been made after a comprehensive state-of-the-art analysis, and includes the design of a Wearable Device Service Bus (WDSB) including the technologies collected in the requirement analysis (ESB, WWBAN, WSN and IoT). Applications are able to access the WSN services regardless of the platform and operating system where they are running. Besides, this proposal also includes the design of a Wearable Inter-Domain communication Protocols set (WIDP) which integrates lightweight protocols suitable to be used in low-capacities devices (REST, JSON, AMQP, CoAP, etc...). Furthermore, a security solution for service management based on a trustworthy domains model to deploy security services in WSNs has been designed. Although the proposal is a generic framework for applications based on services provided by wearable devices, an application scenario for testing purposes has been included. In this validation scenario it has been presented an autonomous physical condition performance system, based on a WSN, bringing the possibility to include several elements in an IoT scenario: a smartwatch, a physiological monitoring device and a smartphone. In summary, the general objective of this thesis is solving the heterogeneity and security challenges arising when developing applications for WSNs and wearable devices. As it has been presented in the thesis, the solution proposed has been successfully validated in a real scenario and the obtained results were satisfactory.

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.

Trust and Privacy Solutions Based on Holistic Service Requirements

The products and services designed for Smart Cities provide the necessary tools to improve the management of modern cities in a more efficient way. These tools need to gather citizens’ information about their activity, preferences, habits, etc. opening up the possibility of tracking them. Thus, privacy and security policies must be developed in order to satisfy and manage the legislative heterogeneity surrounding the services provided and comply with the laws of the country where they are provided. This paper presents one of the possible solutions to manage this heterogeneity, bearing in mind these types of networks, such as Wireless Sensor Networks, have important resource limitations. A knowledge and ontology management system is proposed to facilitate the collaboration between the business, legal and technological areas. This will ease the implementation of adequate specific security and privacy policies for a given service. All these security and privacy policies are based on the information provided by the deployed platforms and by expert system processing.

Combining visual features and Growing Neural Gas networks for robotic 3D SLAM

The use of 3D data in mobile robotics provides valuable information about the robot’s environment. Traditionally, stereo cameras have been used as a low-cost 3D sensor. However, the lack of precision and texture for some surfaces suggests that the use of other 3D sensors could be more suitable. In this work, we examine the use of two sensors: an infrared SR4000 and a Kinect camera. We use a combination of 3D data obtained by these cameras, along with features obtained from 2D images acquired from these cameras, using a Growing Neural Gas (GNG) network applied to the 3D data. The goal is to obtain a robust egomotion technique. The GNG network is used to reduce the camera error. To calculate the egomotion, we test two methods for 3D registration. One is based on an iterative closest points algorithm, and the other employs random sample consensus. Finally, a simultaneous localization and mapping method is applied to the complete sequence to reduce the global error. The error from each sensor and the mapping results from the proposed method are examined.

Efficient Multi-hop Broadcast Data Dissemination in IoT and Smart Cities

Internet of Things (IoT) can be defined as a “network of networks” composed by billions of uniquely identified physical Smart Objects (SO), organized in an Internet-like structure. Smart Objects can be items equipped with sensors, consumer devices (e.g., smartphones, tablets, or wearable devices), and enterprise assets that are connected both to the Internet and to each others. The birth of the IoT, with its communications paradigms, can be considered as an enabling factor for the creation of the so-called Smart Cities. A Smart City uses Information and Communication Technologies (ICT) to enhance quality, performance and interactivity of urban services, ranging from traffic management and pollution monitoring to government services and energy management. This thesis is focused on multi-hop data dissemination within IoT and Smart Cities scenarios. The proposed multi-hop techniques, mostly based on probabilistic forwarding, have been used for different purposes: from the improvement of the performance of unicast protocols for Wireless Sensor Networks (WSNs) to the efficient data dissemination within Vehicular Ad-hoc NETworks (VANETs).