Multi-agent Architecture for Heterogeneous Reasoning under Uncertainty Combining MSBN and Ontologies in Distributed Network Diagnosis

This article proposes a MAS architecture for network diagnosis under uncertainty. Network diagnosis is divided into two inference processes: hypothesis generation and hypothesis confirmation. The first process is distributed among several agents based on a MSBN, while the second one is carried out by agents using semantic reasoning. A diagnosis ontology has been defined in order to combine both inference processes. To drive the deliberation process, dynamic data about the influence of observations are taken during diagnosis process. In order to achieve quick and reliable diagnoses, this influence is used to choose the best action to perform. This approach has been evaluated in a P2P video streaming scenario. Computational and time improvements are highlight as conclusions.

A multi-agent system with distributed bayesian reasoning for network fault diagnosis

In this paper, an innovative approach to perform distributed Bayesian inference using a multi-agent architecture is presented. The final goal is dealing with uncertainty in network diagnosis, but the solution can be of applied in other fields. The validation testbed has been a P2P streaming video service. An assessment of the work is presented, in order to show its advantages when it is compared with traditional manual processes and other previous systems.

Consumo colaborativo. Análisis, estudio de casos de éxito y buenas prácticas

Se pretende estudiar en este Trabajo Fin de Máster la influencia en la sociedad de un fenómeno de actualidad como es el consumo colaborativo. Para ello se han fijado dos objetivos relacionados entre sí. Por un lado profundizar en este nuevo movimiento desde todas sus aristas bajo un punto de vista teórico para conseguir una visión independiente de cada una de ellas así como una visión de conjunto que las relacione. De este modo, a nivel teórico, analizaremos conceptos tan importantes como son los factores claves para su aparición, la creación y modificación de nuevos mercados, sus modelos de negocio, los marketplaces P2P, los riesgos a los que se enfrenta y la financiación de estas iniciativas. Por otro lado, aplicaremos este conocimiento en una segunda parte práctica. Para ello, utilizando como metodología científica el estudio de casos, se analizan una serie de casos de éxito de los más significativos de este movimiento poniendo el foco en el panorama español. Por último extraeremos del análisis unas buenas prácticas que le puedan ser de utilidad a una ‘startup’ en sus primeros pasos. ABSTRACT I intend to study in this research the influence in the society of a new movement, the so called Collaborative Consumption – a form of consumption where people share goods and services. Two related objectives have been set in this context. On the one hand it will be necessary to deep into this new movement from different perspectives under a theoretical point of view to get an independent view of each one as well as an overview that relates all of them. To accomplish this, it will be necessary to discuss important concepts such as the key factors for its occurrence, the creation and modification of new markets, business models, the P2P marketplaces, the risks it faces and the funding part of these initiatives. On the other hand, we will apply this knowledge in a second practical part using the case study as scientific methodology. A series of case studies, the most significant of this movement, will be analyzed focusing on the Spanish landscape. Finally, we will derive from the analysis a set of best practices that could be helpful to a start-up in its first steps.

Automatic fault detection on BIPV systems without solar irradiation data

BIPV systems are small PV generation units spread out over the territory, and whose characteristics are very diverse. This makes difficult a cost-effective procedure for monitoring, fault detection, performance analyses, operation and maintenance. As a result, many problems affecting BIPV systems go undetected. In order to carry out effective automatic fault detection procedures, we need a performance indicator that is reliable and that can be applied on many PV systems at a very low cost. The existing approaches for analyzing the performance of PV systems are often based on the Performance Ratio (PR), whose accuracy depends on good solar irradiation data, which in turn can be very difficult to obtain or cost-prohibitive for the BIPV owner. We present an alternative fault detection procedure based on a performance indicator that can be constructed on the sole basis of the energy production data measured at the BIPV systems. This procedure does not require the input of operating conditions data, such as solar irradiation, air temperature, or wind speed. The performance indicator, called Performance to Peers (P2P), is constructed from spatial and temporal correlations between the energy output of neighboring and similar PV systems. This method was developed from the analysis of the energy production data of approximately 10,000 BIPV systems located in Europe. The results of our procedure are illustrated on the hourly, daily and monthly data monitored during one year at one BIPV system located in the South of Belgium. Our results confirm that it is possible to carry out automatic fault detection procedures without solar irradiation data. P2P proves to be more stable than PR most of the time, and thus constitutes a more reliable performance indicator for fault detection procedures. We also discuss the main limitations of this novel methodology, and we suggest several future lines of research that seem promising to improve on these procedures.

Desarrollo de aplicaciones android usando la tecnología wifi-direct

Este proyecto de fin de grado pretende demostrar la importancia y la utilidad de la creación de redes de dispositivos móviles conectados entre sí. Para ello se explicarán varios tipos de redes inalámbricas que permiten estas conexiones directas entre dispositivos sin la necesidad de un servidor. En estas redes inalámbricas se destacan las redes P2P y las redes Ad-hoc, las cuales se explicarán posteriormente. El despliegue de estas redes se puede encontrar en un amplio rango de campos como puede ser la agricultura, la medicina e incluso en el ámbito militar. Es objetivo de este proyecto, además, el estudio de la tecnología Wi-Fi Direct creada por la Wi-Fi Alliance. Como se explicará a lo largo del proyecto, Wi-Fi Direct está basado en las redes P2P. Esta tecnología permite a los dispositivos cercanos crear redes P2P a través de la red Wi-Fi sin la necesidad de un punto de acceso a Internet. Por otro lado, una gran cantidad de los dispositivos móviles que existen actualmente poseen el sistema operativo Android. Android ha incorporado en sus dispositivos más recientes la tecnología Wi-Fi Direct. Debido a ello han ido surgiendo aplicaciones que usando esta tecnología consiguen desde enviar ficheros hasta indicar la localización de un usuario. Esta tecnología combinada con este tipo de dispositivos puede ser muy útil para utilizar en casos de emergencia donde las infraestructuras de comunicaciones no estén disponibles ya que al no necesitar un punto de acceso a internet es posible la comunicación entre un usuario en peligro y otro que se encuentre dentro de un radio cercano. Por estos motivos otro de los principales objetivos de este proyecto es la implementación de una aplicación para dispositivos Android que use la tecnología Wi-Fi Direct para realizar varias funcionalidades diferentes, como es el intercambio de ficheros entre dispositivos y la creación de un chat para la comunicación simultanea entre dos dispositivos. Con esto se pretende conocer mejor el funcionamiento de la tecnología Wi-Fi Direct y demostrar su utilidad en los dispositivos móviles como son los dispositivos Android. ABSTRACT. This final degree Project tries to demonstrate the importance and utility of networking mobile devices. For this purpose several types of wireless networks will be explained. These networks allow direct connections between devices. The most prominent Wireless networks are P2P and Ad-hoc which will be explained later. The use of these networks can be found in a wide range of fields such as agriculture medicine, and even in the military sector. Besides, other aim of this project is the study of Wi-Fi Direct Technology which is created by Wi-Fi Alliance. As it explained along the project, Wi-Fi Direct is based on P2P networks. This technology lets nearby devices create P2P networks through Wi-Fi network without an Internet access point. On the other hand, a large number of mobile devices have the Android OS. Android has integrated Wi-Fi Direct technology in its latest devices. Because of this applications have emerged that using this technology they get from sending files to send the user’s location. This technology combined with these devices can be very useful to use in emergencies where communications infrastructures are not available. Since not need an Internet access point, communication between a user in danger and another within close radius is possible. For these reasons another of the main aims of this project is the implementation of an application for Android devices which use Wi-Fi Direct technology to perform several different functionalities, such as file exchange or chat for simultaneous communication between devices. This is intended to better understand the operation of Wi-Fi Direct technology and prove its utility on mobile devices such as Android devices.

Clasificación de tráfico de Internet mediante análisis de datos

Poder clasificar de manera precisa la aplicación o programa del que provienen los flujos que conforman el tráfico de uso de Internet dentro de una red permite tanto a empresas como a organismos una útil herramienta de gestión de los recursos de sus redes, así como la posibilidad de establecer políticas de prohibición o priorización de tráfico específico. La proliferación de nuevas aplicaciones y de nuevas técnicas han dificultado el uso de valores conocidos (well-known) en puertos de aplicaciones proporcionados por la IANA (Internet Assigned Numbers Authority) para la detección de dichas aplicaciones. Las redes P2P (Peer to Peer), el uso de puertos no conocidos o aleatorios, y el enmascaramiento de tráfico de muchas aplicaciones en tráfico HTTP y HTTPS con el fin de atravesar firewalls y NATs (Network Address Translation), entre otros, crea la necesidad de nuevos métodos de detección de tráfico. El objetivo de este estudio es desarrollar una serie de prácticas que permitan realizar dicha tarea a través de técnicas que están más allá de la observación de puertos y otros valores conocidos. Existen una serie de metodologías como Deep Packet Inspection (DPI) que se basa en la búsqueda de firmas, signatures, en base a patrones creados por el contenido de los paquetes, incluido el payload, que caracterizan cada aplicación. Otras basadas en el aprendizaje automático de parámetros de los flujos, Machine Learning, que permite determinar mediante análisis estadísticos a qué aplicación pueden pertenecer dichos flujos y, por último, técnicas de carácter más heurístico basadas en la intuición o el conocimiento propio sobre tráfico de red. En concreto, se propone el uso de alguna de las técnicas anteriormente comentadas en conjunto con técnicas de minería de datos como son el Análisis de Componentes Principales (PCA por sus siglas en inglés) y Clustering de estadísticos extraídos de los flujos procedentes de ficheros de tráfico de red. Esto implicará la configuración de diversos parámetros que precisarán de un proceso iterativo de prueba y error que permita dar con una clasificación del tráfico fiable. El resultado ideal sería aquel en el que se pudiera identificar cada aplicación presente en el tráfico en un clúster distinto, o en clusters que agrupen grupos de aplicaciones de similar naturaleza. Para ello, se crearán capturas de tráfico dentro de un entorno controlado e identificando cada tráfico con su aplicación correspondiente, a continuación se extraerán los flujos de dichas capturas. Tras esto, parámetros determinados de los paquetes pertenecientes a dichos flujos serán obtenidos, como por ejemplo la fecha y hora de llagada o la longitud en octetos del paquete IP. Estos parámetros serán cargados en una base de datos MySQL y serán usados para obtener estadísticos que ayuden, en un siguiente paso, a realizar una clasificación de los flujos mediante minería de datos. Concretamente, se usarán las técnicas de PCA y clustering haciendo uso del software RapidMiner. Por último, los resultados obtenidos serán plasmados en una matriz de confusión que nos permitirá que sean valorados correctamente. ABSTRACT. Being able to classify the applications that generate the traffic flows in an Internet network allows companies and organisms to implement efficient resource management policies such as prohibition of specific applications or prioritization of certain application traffic, looking for an optimization of the available bandwidth. The proliferation of new applications and new technics in the last years has made it more difficult to use well-known values assigned by the IANA (Internet Assigned Numbers Authority), like UDP and TCP ports, to identify the traffic. Also, P2P networks and data encapsulation over HTTP and HTTPS traffic has increased the necessity to improve these traffic analysis technics. The aim of this project is to develop a number of techniques that make us able to classify the traffic with more than the simple observation of the well-known ports. There are some proposals that have been created to cover this necessity; Deep Packet Inspection (DPI) tries to find signatures in the packets reading the information contained in them, the payload, looking for patterns that can be used to characterize the applications to which that traffic belongs; Machine Learning procedures work with statistical analysis of the flows, trying to generate an automatic process that learns from those statistical parameters and calculate the likelihood of a flow pertaining to a certain application; Heuristic Techniques, finally, are based in the intuition or the knowledge of the researcher himself about the traffic being analyzed that can help him to characterize the traffic. Specifically, the use of some of the techniques previously mentioned in combination with data mining technics such as Principal Component Analysis (PCA) and Clustering (grouping) of the flows extracted from network traffic captures are proposed. An iterative process based in success and failure will be needed to configure these data mining techniques looking for a reliable traffic classification. The perfect result would be the one in which the traffic flows of each application is grouped correctly in each cluster or in clusters that contain group of applications of similar nature. To do this, network traffic captures will be created in a controlled environment in which every capture is classified and known to pertain to a specific application. Then, for each capture, all the flows will be extracted. These flows will be used to extract from them information such as date and arrival time or the IP length of the packets inside them. This information will be then loaded to a MySQL database where all the packets defining a flow will be classified and also, each flow will be assigned to its specific application. All the information obtained from the packets will be used to generate statistical parameters in order to describe each flow in the best possible way. After that, data mining techniques previously mentioned (PCA and Clustering) will be used on these parameters making use of the software RapidMiner. Finally, the results obtained from the data mining will be compared with the real classification of the flows that can be obtained from the database. A Confusion Matrix will be used for the comparison, letting us measure the veracity of the developed classification process.

Lightweight peer-to-peer secure multi-party VoIP protocol

Multi-party voice-over-IP (MVoIP) services provide economical and convenient group communication mechanisms for many emerging applications such as distance collaboration systems, on-line meetings and Internet gaming. In this paper, we present a light peer-to-peer (P2P) protocol to provide MVoIP services on small platforms like mobile phones and PDAs. Unlike other proposals, our solution is fully distributed and self-organizing without requiring specialized servers or IP multicast support.

Protocolo multiplataforma no centralizado para comunicaciones multimedia seguras

En este trabajo se propone y desarrolla una topología en k-hipercubos que resuelve los principales inconvenientes asociados a la topología en hipercubo convencional. Los resultados obtenidos son muy prometedores, con aplicaciones tanto en el campo de la voz sobre IP, como en muchos otros campos que precisen de un intercambio de información muchos a muchos. Sobre la topología propuesta se define el protocolo Darkcube, que es una propuesta de protocolo totalmente distribuido basado en el concepto de darknet, posibilitando la realización de conversaciones muchos a muchos incluyendo audio, vídeo, texto y datos de geoposicionamiento, entre otros. También se propone un método de codificación de coordenadas de geoposicionamiento que resulta especialmente eficiente en el aprovechamiento del ancho de banda sobrante en las comunicaciones muchos a muchos que proporciona Darkcube. Durante el desarrollo de este trabajo, se ha implementado el simulador DarkcubeEmu; herramienta que posibilita la obtención de resultados relevantes en términos de la calidad de la comunicación. Finalmente, utilizando como base el protocolo Darkcube, se propone un protocolo de seguridad que traslada un esquema de infraestructura de clave pública a un protocolo totalmente distribuido, como es Darkcube; garantizando, de esta forma, la confidencialidad en las comunicaciones y la legitimidad de la identidad asociada a cada uno de sus miembros.

The Business Models and Economics of Peer-to-Peer lending. ECRI Research Report No 17, May 2016

This paper reviews peer-to-peer (P2P) lending, its development in the UK and other countries, and assesses the business and economic policy issues surrounding this new form of intermediation. P2P platform technology allows direct matching of borrowers’ and lenders’ diversification over a large number of borrowers without the loans having to be held on an intermediary balance sheet. P2P lending has developed rapidly in both the US and the UK, but it still represents a small fraction, less than 1%, of the stock of bank lending. In the UK – but not elsewhere – it is an important source of loans for smaller companies. We argue that P2P lending is fundamentally complementary to, and not competitive with, conventional banking. We therefore expect banks to adapt to the emergence of P2P lending, either by cooperating closely with third-party P2P lending platforms or offering their own proprietary platforms. We also argue that the full development of the sector requires much further work addressing the risks and business and regulatory issues in P2P lending, including risk communication, orderly resolution of platform failure, control of liquidity risks and minimisation of fraud, security and operational risks. This will depend on developing reliable business processes, the promotion to the full extent possible of transparency and standardisation and appropriate regulation that serves the needs of customers.

Towards Automation in Digital Investigations : Seeking Efficiency in Digital Forensics in Mobile and Cloud Environments

Cybercrime and related malicious activity in our increasingly digital world has become more prevalent and sophisticated, evading traditional security mechanisms. Digital forensics has been proposed to help investigate, understand and eventually mitigate such attacks. The practice of digital forensics, however, is still fraught with various challenges. Some of the most prominent of these challenges include the increasing amounts of data and the diversity of digital evidence sources appearing in digital investigations. Mobile devices and cloud infrastructures are an interesting specimen, as they inherently exhibit these challenging circumstances and are becoming more prevalent in digital investigations today. Additionally they embody further characteristics such as large volumes of data from multiple sources, dynamic sharing of resources, limited individual device capabilities and the presence of sensitive data. These combined set of circumstances make digital investigations in mobile and cloud environments particularly challenging. This is not aided by the fact that digital forensics today still involves manual, time consuming tasks within the processes of identifying evidence, performing evidence acquisition and correlating multiple diverse sources of evidence in the analysis phase. Furthermore, industry standard tools developed are largely evidence-oriented, have limited support for evidence integration and only automate certain precursory tasks, such as indexing and text searching. In this study, efficiency, in the form of reducing the time and human labour effort expended, is sought after in digital investigations in highly networked environments through the automation of certain activities in the digital forensic process. To this end requirements are outlined and an architecture designed for an automated system that performs digital forensics in highly networked mobile and cloud environments. Part of the remote evidence acquisition activity of this architecture is built and tested on several mobile devices in terms of speed and reliability. A method for integrating multiple diverse evidence sources in an automated manner, supporting correlation and automated reasoning is developed and tested. Finally the proposed architecture is reviewed and enhancements proposed in order to further automate the architecture by introducing decentralization particularly within the storage and processing functionality. This decentralization also improves machine to machine communication supporting several digital investigation processes enabled by the architecture through harnessing the properties of various peer-to-peer overlays. Remote evidence acquisition helps to improve the efficiency (time and effort involved) in digital investigations by removing the need for proximity to the evidence. Experiments show that a single TCP connection client-server paradigm does not offer the required scalability and reliability for remote evidence acquisition and that a multi-TCP connection paradigm is required. The automated integration, correlation and reasoning on multiple diverse evidence sources demonstrated in the experiments improves speed and reduces the human effort needed in the analysis phase by removing the need for time-consuming manual correlation. Finally, informed by published scientific literature, the proposed enhancements for further decentralizing the Live Evidence Information Aggregator (LEIA) architecture offer a platform for increased machine-to-machine communication thereby enabling automation and reducing the need for manual human intervention.

PROST: A programmable structured peer-to-peer overlay network

We present the idea of a programmable structured P2P architecture. Our proposed system allows the key-based routing infrastructure, which is common to all structured P2P overlays, to be shared by multiple applications. Furthermore, our architecture allows the dynamic and on-demand deployment of new applications and services on top of the shared routing layer.

An Autonomic Framework for Mobile Cloud Computing

This thesis presents the formal definition of a novel Mobile Cloud Computing (MCC) extension of the Networked Autonomic Machine (NAM) framework, a general-purpose conceptual tool which describes large-scale distributed autonomic systems. The introduction of autonomic policies in the MCC paradigm has proved to be an effective technique to increase the robustness and flexibility of MCC systems. In particular, autonomic policies based on continuous resource and connectivity monitoring help automate context-aware decisions for computation offloading. We have also provided NAM with a formalization in terms of a transformational operational semantics in order to fill the gap between its existing Java implementation NAM4J and its conceptual definition. Moreover, we have extended NAM4J by adding several components with the purpose of managing large scale autonomic distributed environments. In particular, the middleware allows for the implementation of peer-to-peer (P2P) networks of NAM nodes. Moreover, NAM mobility actions have been implemented to enable the migration of code, execution state and data. Within NAM4J, we have designed and developed a component, denoted as context bus, which is particularly useful in collaborative applications in that, if replicated on each peer, it instantiates a virtual shared channel allowing nodes to notify and get notified about context events. Regarding the autonomic policies management, we have provided NAM4J with a rule engine, whose purpose is to allow a system to autonomously determine when offloading is convenient. We have also provided NAM4J with trust and reputation management mechanisms to make the middleware suitable for applications in which such aspects are of great interest. To this purpose, we have designed and implemented a distributed framework, denoted as DARTSense, where no central server is required, as reputation values are stored and updated by participants in a subjective fashion. We have also investigated the literature regarding MCC systems. The analysis pointed out that all MCC models focus on mobile devices, and consider the Cloud as a system with unlimited resources. To contribute in filling this gap, we defined a modeling and simulation framework for the design and analysis of MCC systems, encompassing both their sides. We have also implemented a modular and reusable simulator of the model. We have applied the NAM principles to two different application scenarios. First, we have defined a hybrid P2P/cloud approach where components and protocols are autonomically configured according to specific target goals, such as cost-effectiveness, reliability and availability. Merging P2P and cloud paradigms brings together the advantages of both: high availability, provided by the Cloud presence, and low cost, by exploiting inexpensive peers resources. As an example, we have shown how the proposed approach can be used to design NAM-based collaborative storage systems based on an autonomic policy to decide how to distribute data chunks among peers and Cloud, according to cost minimization and data availability goals. As a second application, we have defined an autonomic architecture for decentralized urban participatory sensing (UPS) which bridges sensor networks and mobile systems to improve effectiveness and efficiency. The developed application allows users to retrieve and publish different types of sensed information by using the features provided by NAM4J's context bus. Trust and reputation is managed through the application of DARTSense mechanisms. Also, the application includes an autonomic policy that detects areas characterized by few contributors, and tries to recruit new providers by migrating code necessary to sensing, through NAM mobility actions.

Implications of query caching for JXTA peers

This dissertation studies the caching of queries and how to cache in an efficient way, so that retrieving previously accessed data does not need any intermediary nodes between the data-source peer and the querying peer in super-peer P2P network. A precise algorithm was devised that demonstrated how queries can be deconstructed to provide greater flexibility for reusing their constituent elements. It showed how subsequent queries can make use of more than one previous query and any part of those queries to reconstruct direct data communication with one or more source peers that have supplied data previously. In effect, a new query can search and exploit the entire cached list of queries to construct the list of the data locations it requires that might match any locations previously accessed. The new method increases the likelihood of repeat queries being able to reuse earlier queries and provides a viable way of by-passing shared data indexes in structured networks. It could also increase the efficiency of unstructured networks by reducing traffic and the propensity for network flooding. In addition, performance evaluation for predicting query routing performance by using a UML sequence diagram is introduced. This new method of performance evaluation provides designers with information about when it is most beneficial to use caching and how the peer connections can optimize its exploitation.

Characterizing Internet worm spatial-temporal infection structures

Since the Morris worm was released in 1988, Internet worms continue to be one of top security threats. For example, the Conficker worm infected 9 to 15 million machines in early 2009 and shut down the service of some critical government and medical networks. Moreover, it constructed a massive peer-to-peer (P2P) botnet. Botnets are zombie networks controlled by attackers setting out coordinated attacks. In recent years, botnets have become the number one threat to the Internet. The objective of this research is to characterize spatial-temporal infection structures of Internet worms, and apply the observations to study P2P-based botnets formed by worm infection. First, we infer temporal characteristics of the Internet worm infection structure, i.e., the host infection time and the worm infection sequence, and thus pinpoint patient zero or initially infected hosts. Specifically, we apply statistical estimation techniques on Darknet observations. We show analytically and empirically that our proposed estimators can significantly improve the inference accuracy. Second, we reveal two key spatial characteristics of the Internet worm infection structure, i.e., the number of children and the generation of the underlying tree topology formed by worm infection. Specifically, we apply probabilistic modeling methods and a sequential growth model. We show analytically and empirically that the number of children has asymptotically a geometric distribution with parameter 0.5, and the generation follows closely a Poisson distribution. Finally, we evaluate bot detection strategies and effects of user defenses in P2P-based botnets formed by worm infection. Specifically, we apply the observations of the number of children and demonstrate analytically and empirically that targeted detection that focuses on the nodes with the largest number of children is an efficient way to expose bots. However, we also point out that future botnets may self-stop scanning to weaken targeted detection, without greatly slowing down the speed of worm infection. We then extend the worm spatial infection structure and show empirically that user defenses, e.g. , patching or cleaning, can significantly mitigate the robustness and the effectiveness of P2P-based botnets. To counterattack, we evaluate a simple measure by future botnets that enhances topology robustness through worm re-infection.