A Dataset for Evaluating Intrusion Detection Systems in IEEE 802.11 Wireless Networks

Internet access by wireless networks has grown considerably in recent years. However, these networks are vulnerable to security problems, especially those related to denial of service attacks. Intrusion Detection Systems(IDS)are widely used to improve network security, but comparison among the several existing approaches is not a trivial task. This paper proposes building a datasetfor evaluating IDS in wireless environments. The data were captured in a real, operating network. We conducted tests using traditional IDS and achieved great results, which showed the effectiveness of our proposed approach.

Classification algorithms for Intelligent Transport Systems

Intelligent Transport Systems (ITS) consists in the application of ICT to transport to offer new and improved services to the mobility of people and freights. While using ITS, travellers produce large quantities of data that can be collected and analysed to study their behaviour and to provide information to decision makers and planners. The thesis proposes innovative deployments of classification algorithms for Intelligent Transport System with the aim to support the decisions on traffic rerouting, bus transport demand and behaviour of two wheelers vehicles. The first part of this work provides an overview and a classification of a selection of clustering algorithms that can be implemented for the analysis of ITS data. The first contribution of this thesis is an innovative use of the agglomerative hierarchical clustering algorithm to classify similar travels in terms of their origin and destination, together with the proposal for a methodology to analyse drivers’ route choice behaviour using GPS coordinates and optimal alternatives. The clusters of repetitive travels made by a sample of drivers are then analysed to compare observed route choices to the modelled alternatives. The results of the analysis show that drivers select routes that are more reliable but that are more expensive in terms of travel time. Successively, different types of users of a service that provides information on the real time arrivals of bus at stop are classified using Support Vector Machines. The results shows that the results of the classification of different types of bus transport users can be used to update or complement the census on bus transport flows. Finally, the problem of the classification of accidents made by two wheelers vehicles is presented together with possible future application of clustering methodologies aimed at identifying and classifying the different types of accidents.

A Flow Trace Generator using Graph-based Traffic Classification Techniques

We propose a novel methodology to generate realistic network flow traces to enable systematic evaluation of network monitoring systems in various traffic conditions. Our technique uses a graph-based approach to model the communication structure observed in real-world traces and to extract traffic templates. By combining extracted and user-defined traffic templates, realistic network flow traces that comprise normal traffic and customized conditions are generated in a scalable manner. A proof-of-concept implementation demonstrates the utility and simplicity of our method to produce a variety of evaluation scenarios. We show that the extraction of templates from real-world traffic leads to a manageable number of templates that still enable accurate re-creation of the original communication properties on the network flow level.

Comparison of different radiography systems in an experimental study for detection of forearm fractures and evaluation of the Müller-AO and Frykman classification for distal radius fractures

OBJECTIVES: We sought to compare the diagnostic performance of screen-film radiography, storage-phosphor radiography, and a flat-panel detector system in detecting forearm fractures and to classify distal radius fractures according to the Müller-AO and Frykman classifications compared with the true extent, depicted by anatomic preparation. MATERIALS AND METHODS: A total of 71 cadaver arms were fractured in a material testing machine creating different fractures of the radius and ulna as well as of the carpal bones. Radiographs of the complete forearm were evaluated by 3 radiologists, and anatomic preparation was used as standard of reference in a receiver operating curve analysis. RESULTS: The highest diagnostic performance was obtained for the detection of distal radius fractures with area under the receiver operating curve (AUC) values of 0.959 for screen-film radiography, 0.966 for storage-phosphor radiography, and 0.971 for the flat-panel detector system (P > 0.05). Exact classification was slightly better for the Frykman (kappa values of 0.457-0.478) compared with the Müller-AO classification (kappa values of 0.404-0.447), but agreement can be considered as moderate for both classifications. CONCLUSIONS: The 3 imaging systems showed a comparable diagnostic performance in detecting forearm fractures. A high diagnostic performance was demonstrated for distal radius fractures and conventional radiography can be routinely performed for fracture detection. However, compared with anatomic preparation, depiction of the true extent of distal radius fractures was limited and the severity of distal radius fractures tends to be underestimated.

Improving Management of Distributed Services Using Correlations and Predictions in SLA-Driven Cloud Computing Systems

Recent advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing environmental conditions and number of users, application performance might suffer, leading to Service Level Agreement (SLA) violations and inefficient use of hardware resources. We introduce a system for controlling the complexity of scaling applications composed of multiple services using mechanisms based on fulfillment of SLAs. We present how service monitoring information can be used in conjunction with service level objectives, predictions, and correlations between performance indicators for optimizing the allocation of services belonging to distributed applications. We validate our models using experiments and simulations involving a distributed enterprise information system. We show how discovering correlations between application performance indicators can be used as a basis for creating refined service level objectives, which can then be used for scaling the application and improving the overall application's performance under similar conditions.

Cloud Computing Service for Managing Large Medical Image Data-Sets Using Balanced Collaborative Agents

Managing large medical image collections is an increasingly demanding important issue in many hospitals and other medical settings. A huge amount of this information is daily generated, which requires robust and agile systems. In this paper we present a distributed multi-agent system capable of managing very large medical image datasets. In this approach, agents extract low-level information from images and store them in a data structure implemented in a relational database. The data structure can also store semantic information related to images and particular regions. A distinctive aspect of our work is that a single image can be divided so that the resultant sub-images can be stored and managed separately by different agents to improve performance in data accessing and processing. The system also offers the possibility of applying some region-based operations and filters on images, facilitating image classification. These operations can be performed directly on data structures in the database.

Contribution to multiuser videoconferencing systems based on cloud computing

Multi-user videoconferencing systems offer communication between more than two users, who are able to interact through their webcams, microphones and other components. The use of these systems has been increased recently due to, on the one hand, improvements in Internet access, networks of companies, universities and houses, whose available bandwidth has been increased whilst the delay in sending and receiving packets has decreased. On the other hand, the advent of Rich Internet Applications (RIA) means that a large part of web application logic and control has started to be implemented on the web browsers. This has allowed developers to create web applications with a level of complexity comparable to traditional desktop applications, running on top of the Operating Systems. More recently the use of Cloud Computing systems has improved application scalability and involves a reduction in the price of backend systems. This offers the possibility of implementing web services on the Internet with no need to spend a lot of money when deploying infrastructures and resources, both hardware and software. Nevertheless there are not many initiatives that aim to implement videoconferencing systems taking advantage of Cloud systems. This dissertation proposes a set of techniques, interfaces and algorithms for the implementation of videoconferencing systems in public and private Cloud Computing infrastructures. The mechanisms proposed here are based on the implementation of a basic videoconferencing system that runs on the web browser without any previous installation requirements. To this end, the development of this thesis starts from a RIA application with current technologies that allow users to access their webcams and microphones from the browser, and to send captured data through their Internet connections. Furthermore interfaces have been implemented to allow end users to participate in videoconferencing rooms that are managed in different Cloud provider servers. To do so this dissertation starts from the results obtained from the previous techniques and backend resources were implemented in the Cloud. A traditional videoconferencing service which was implemented in the department was modified to meet typical Cloud Computing infrastructure requirements. This allowed us to validate whether Cloud Computing public infrastructures are suitable for the traffic generated by this kind of system. This analysis focused on the network level and processing capacity and stability of the Cloud Computing systems. In order to improve this validation several other general considerations were taken in order to cover more cases, such as multimedia data processing in the Cloud, as research activity has increased in this area in recent years. The last stage of this dissertation is the design of a new methodology to implement these kinds of applications in hybrid clouds reducing the cost of videoconferencing systems. Finally, this dissertation opens up a discussion about the conclusions obtained throughout this study, resulting in useful information from the different stages of the implementation of videoconferencing systems in Cloud Computing systems. RESUMEN Los sistemas de videoconferencia multiusuario permiten la comunicación entre más de dos usuarios que pueden interactuar a través de cámaras de video, micrófonos y otros elementos. En los últimos años el uso de estos sistemas se ha visto incrementado gracias, por un lado, a la mejora de las redes de acceso en las conexiones a Internet en empresas, universidades y viviendas, que han visto un aumento del ancho de banda disponible en dichas conexiones y una disminución en el retardo experimentado por los datos enviados y recibidos. Por otro lado también ayudó la aparación de las Aplicaciones Ricas de Internet (RIA) con las que gran parte de la lógica y del control de las aplicaciones web comenzó a ejecutarse en los mismos navegadores. Esto permitió a los desarrolladores la creación de aplicaciones web cuya complejidad podía compararse con la de las tradicionales aplicaciones de escritorio, ejecutadas directamente por los sistemas operativos. Más recientemente el uso de sistemas de Cloud Computing ha mejorado la escalabilidad y el abaratamiento de los costes para sistemas de backend, ofreciendo la posibilidad de implementar servicios Web en Internet sin la necesidad de grandes desembolsos iniciales en las áreas de infraestructuras y recursos tanto hardware como software. Sin embargo no existen aún muchas iniciativas con el objetivo de realizar sistemas de videoconferencia que aprovechen las ventajas del Cloud. Esta tesis doctoral propone un conjunto de técnicas, interfaces y algoritmos para la implentación de sistemas de videoconferencia en infraestructuras tanto públicas como privadas de Cloud Computing. Las técnicas propuestas en la tesis se basan en la realización de un servicio básico de videoconferencia que se ejecuta directamente en el navegador sin la necesidad de instalar ningún tipo de aplicación de escritorio. Para ello el desarrollo de esta tesis parte de una aplicación RIA con tecnologías que hoy en día permiten acceder a la cámara y al micrófono directamente desde el navegador, y enviar los datos que capturan a través de la conexión de Internet. Además se han implementado interfaces que permiten a usuarios finales la participación en salas de videoconferencia que se ejecutan en servidores de proveedores de Cloud. Para ello se partió de los resultados obtenidos en las técnicas anteriores de ejecución de aplicaciones en el navegador y se implementaron los recursos de backend en la nube. Además se modificó un servicio ya existente implementado en el departamento para adaptarlo a los requisitos típicos de las infraestructuras de Cloud Computing. Alcanzado este punto se procedió a analizar si las infraestructuras propias de los proveedores públicos de Cloud Computing podrían soportar el tráfico generado por los sistemas que se habían adaptado. Este análisis se centró tanto a nivel de red como a nivel de capacidad de procesamiento y estabilidad de los sistemas. Para los pasos de análisis y validación de los sistemas Cloud se tomaron consideraciones más generales para abarcar casos como el procesamiento de datos multimedia en la nube, campo en el que comienza a haber bastante investigación en los últimos años. Como último paso se ideó una metodología de implementación de este tipo de aplicaciones para que fuera posible abaratar los costes de los sistemas de videoconferencia haciendo uso de clouds híbridos. Finalmente en la tesis se abre una discusión sobre las conclusiones obtenidas a lo largo de este amplio estudio, obteniendo resultados útiles en las distintas etapas de implementación de los sistemas de videoconferencia en la nube.

Classification of discrete systems on a square lattice

We consider the classification up to a Möbius transformation of real linearizable and integrable partial difference equations with dispersion defined on a square lattice by the multiscale reduction around their harmonic solution. We show that the A1, A2, and A3 linearizability and integrability conditions constrain the number of parameters in the equation, but these conditions are insufficient for a complete characterization of the subclass of multilinear equations on a square lattice.

Adaptive neuro-fuzzy inference systems (ANFIS) for supervised classification of competence in MIS based on psychomotor skills

INTRODUCTION: Objective assessment of motor skills has become an important challenge in minimally invasive surgery (MIS) training.Currently, there is no gold standard defining and determining the residents' surgical competence.To aid in the decision process, we analyze the validity of a supervised classifier to determine the degree of MIS competence based on assessment of psychomotor skills METHODOLOGY: The ANFIS is trained to classify performance in a box trainer peg transfer task performed by two groups (expert/non expert). There were 42 participants included in the study: the non-expert group consisted of 16 medical students and 8 residents (< 10 MIS procedures performed), whereas the expert group consisted of 14 residents (> 10 MIS procedures performed) and 4 experienced surgeons. Instrument movements were captured by means of the Endoscopic Video Analysis (EVA) tracking system. Nine motion analysis parameters (MAPs) were analyzed, including time, path length, depth, average speed, average acceleration, economy of area, economy of volume, idle time and motion smoothness. Data reduction was performed by means of principal component analysis, and then used to train the ANFIS net. Performance was measured by leave one out cross validation. RESULTS: The ANFIS presented an accuracy of 80.95%, where 13 experts and 21 non-experts were correctly classified. Total root mean square error was 0.88, while the area under the classifiers' ROC curve (AUC) was measured at 0.81. DISCUSSION: We have shown the usefulness of ANFIS for classification of MIS competence in a simple box trainer exercise. The main advantage of using ANFIS resides in its continuous output, which allows fine discrimination of surgical competence. There are, however, challenges that must be taken into account when considering use of ANFIS (e.g. training time, architecture modeling). Despite this, we have shown discriminative power of ANFIS for a low-difficulty box trainer task, regardless of the individual significances between MAPs. Future studies are required to confirm the findings, inclusion of new tasks, conditions and sample population.

Analysis of service-oriented computing systems

La computación basada en servicios (Service-Oriented Computing, SOC) se estableció como un paradigma ampliamente aceptado para el desarollo de sistemas de software flexibles, distribuidos y adaptables, donde las composiciones de los servicios realizan las tareas más complejas o de nivel más alto, frecuentemente tareas inter-organizativas usando los servicios atómicos u otras composiciones de servicios. En tales sistemas, las propriedades de la calidad de servicio (Quality of Service, QoS), como la rapídez de procesamiento, coste, disponibilidad o seguridad, son críticas para la usabilidad de los servicios o sus composiciones en cualquier aplicación concreta. El análisis de estas propriedades se puede realizarse de una forma más precisa y rica en información si se utilizan las técnicas de análisis de programas, como el análisis de complejidad o de compartición de datos, que son capables de analizar simultáneamente tanto las estructuras de control como las de datos, dependencias y operaciones en una composición. El análisis de coste computacional para la composicion de servicios puede ayudar a una monitorización predictiva así como a una adaptación proactiva a través de una inferencia automática de coste computacional, usando los limites altos y bajos como funciones del valor o del tamaño de los mensajes de entrada. Tales funciones de coste se pueden usar para adaptación en la forma de selección de los candidatos entre los servicios que minimizan el coste total de la composición, basado en los datos reales que se pasan al servicio. Las funciones de coste también pueden ser combinadas con los parámetros extraídos empíricamente desde la infraestructura, para producir las funciones de los límites de QoS sobre los datos de entrada, cuales se pueden usar para previsar, en el momento de invocación, las violaciones de los compromisos al nivel de servicios (Service Level Agreements, SLA) potenciales or inminentes. En las composiciones críticas, una previsión continua de QoS bastante eficaz y precisa se puede basar en el modelado con restricciones de QoS desde la estructura de la composition, datos empiricos en tiempo de ejecución y (cuando estén disponibles) los resultados del análisis de complejidad. Este enfoque se puede aplicar a las orquestaciones de servicios con un control centralizado del flujo, así como a las coreografías con participantes multiples, siguiendo unas interacciones complejas que modifican su estado. El análisis del compartición de datos puede servir de apoyo para acciones de adaptación, como la paralelización, fragmentación y selección de los componentes, las cuales son basadas en dependencias funcionales y en el contenido de información en los mensajes, datos internos y las actividades de la composición, cuando se usan construcciones de control complejas, como bucles, bifurcaciones y flujos anidados. Tanto las dependencias funcionales como el contenido de información (descrito a través de algunos atributos definidos por el usuario) se pueden expresar usando una representación basada en la lógica de primer orden (claúsulas de Horn), y los resultados del análisis se pueden interpretar como modelos conceptuales basados en retículos. ABSTRACT Service-Oriented Computing (SOC) is a widely accepted paradigm for development of flexible, distributed and adaptable software systems, in which service compositions perform more complex, higher-level, often cross-organizational tasks using atomic services or other service compositions. In such systems, Quality of Service (QoS) properties, such as the performance, cost, availability or security, are critical for the usability of services and their compositions in concrete applications. Analysis of these properties can become more precise and richer in information, if it employs program analysis techniques, such as the complexity and sharing analyses, which are able to simultaneously take into account both the control and the data structures, dependencies, and operations in a composition. Computation cost analysis for service composition can support predictive monitoring and proactive adaptation by automatically inferring computation cost using the upper and lower bound functions of value or size of input messages. These cost functions can be used for adaptation by selecting service candidates that minimize total cost of the composition, based on the actual data that is passed to them. The cost functions can also be combined with the empirically collected infrastructural parameters to produce QoS bounds functions of input data that can be used to predict potential or imminent Service Level Agreement (SLA) violations at the moment of invocation. In mission-critical applications, an effective and accurate continuous QoS prediction, based on continuations, can be achieved by constraint modeling of composition QoS based on its structure, known data at runtime, and (when available) the results of complexity analysis. This approach can be applied to service orchestrations with centralized flow control, and choreographies with multiple participants with complex stateful interactions. Sharing analysis can support adaptation actions, such as parallelization, fragmentation, and component selection, which are based on functional dependencies and information content of the composition messages, internal data, and activities, in presence of complex control constructs, such as loops, branches, and sub-workflows. Both the functional dependencies and the information content (described using user-defined attributes) can be expressed using a first-order logic (Horn clause) representation, and the analysis results can be interpreted as a lattice-based conceptual models.

Resilience in Cloud Computing for Critical Systems. Resilience, Dependability, Reliability in the use of Cloud Computing in Critical Systems in Public Organizations.

La informática se está convirtiendo en la quinta utilidad (gas, agua, luz, teléfono) en parte debido al impacto de Cloud Computing en las mayorías de las organizaciones. Este uso de informática es usada por cada vez más tipos de sistemas, incluidos Sistemas Críticos. Esto tiene un impacto en la complejidad internad y la fiabilidad de los sistemas de la organización y los que se ofrecen a los clientes. Este trabajo investiga el uso de Cloud Computing por sistemas críticos, centrándose en las dependencias y especialmente en la fiabilidad de estos sistemas. Se han presentado algunos ejemplos de su uso, y aunque su utilización en sistemas críticos no está extendido, se presenta cual puede llegar a ser su impacto. El objetivo de este trabajo es primero definir un modelo que pueda representar de una forma cuantitativa las interdependencias en fiabilidad y interdependencia para las organizaciones que utilicen estos sistemas, y aplicar este modelo en un sistema crítico del campo de sanidad y mostrar sus resultados. Los conceptos de “macro-dependability” y “micro-dependability” son introducidos en el modelo para la definición de interdependencia y para analizar la fiabilidad de sistemas que dependen de otros sistemas. ABSTRACT With the increasing utilization of Internet services and cloud computing by most organizations (both private and public), it is clear that computing is becoming the 5th utility (along with water, electricity, telephony and gas). These technologies are used for almost all types of systems, and the number is increasing, including Critical Infrastructure systems. Even if Critical Infrastructure systems appear not to rely directly on cloud services, there may be hidden inter-dependencies. This is true even for private cloud computing, which seems more secure and reliable. The critical systems can began in some cases with a clear and simple design, but evolved as described by Egan to "rafted" networks. Because they are usually controlled by one or few organizations, even when they are complex systems, their dependencies can be understood. The organization oversees and manages changes. These CI systems have been affected by the introduction of new ICT models like global communications, PCs and the Internet. Even virtualization took more time to be adopted by Critical systems, due to their strategic nature, but once that these technologies have been proven in other areas, at the end they are adopted as well, for different reasons such as costs. A new technology model is happening now based on some previous technologies (virtualization, distributing and utility computing, web and software services) that are offered in new ways and is called cloud computing. The organizations are migrating more services to the cloud; this will have impact in their internal complexity and in the reliability of the systems they are offering to the organization itself and their clients. Not always this added complexity and associated risks to their reliability are seen. As well, when two or more CI systems are interacting, the risks of one can affect the rest, sharing the risks. This work investigates the use of cloud computing by critical systems, and is focused in the dependencies and reliability of these systems. Some examples are presented together with the associated risks. A framework is introduced for analysing the dependability and resilience of a system that relies on cloud services and how to improve them. As part of the framework, the concepts of micro and macro dependability are introduced to explain the internal and external dependability on services supplied by an external cloud. A pharmacovigilance model system has been used for framework validation.

Automatic blood glucose classification for gestational diabetes with feature selection: decision trees vs neural networks

Automatic blood glucose classification may help specialists to provide a better interpretation of blood glucose data, downloaded directly from patients glucose meter and will contribute in the development of decision support systems for gestational diabetes. This paper presents an automatic blood glucose classifier for gestational diabetes that compares 6 different feature selection methods for two machine learning algorithms: neural networks and decision trees. Three searching algorithms, Greedy, Best First and Genetic, were combined with two different evaluators, CSF and Wrapper, for the feature selection. The study has been made with 6080 blood glucose measurements from 25 patients. Decision trees with a feature set selected with the Wrapper evaluator and the Best first search algorithm obtained the best accuracy: 95.92%.