1,257 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    Undergraduate Catalog of Studies, 2023-2024

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    Graduate Catalog of Studies, 2023-2024

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    Multidisciplinary perspectives on Artificial Intelligence and the law

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    This open access book presents an interdisciplinary, multi-authored, edited collection of chapters on Artificial Intelligence (‘AI’) and the Law. AI technology has come to play a central role in the modern data economy. Through a combination of increased computing power, the growing availability of data and the advancement of algorithms, AI has now become an umbrella term for some of the most transformational technological breakthroughs of this age. The importance of AI stems from both the opportunities that it offers and the challenges that it entails. While AI applications hold the promise of economic growth and efficiency gains, they also create significant risks and uncertainty. The potential and perils of AI have thus come to dominate modern discussions of technology and ethics – and although AI was initially allowed to largely develop without guidelines or rules, few would deny that the law is set to play a fundamental role in shaping the future of AI. As the debate over AI is far from over, the need for rigorous analysis has never been greater. This book thus brings together contributors from different fields and backgrounds to explore how the law might provide answers to some of the most pressing questions raised by AI. An outcome of the Católica Research Centre for the Future of Law and its interdisciplinary working group on Law and Artificial Intelligence, it includes contributions by leading scholars in the fields of technology, ethics and the law.info:eu-repo/semantics/publishedVersio

    Undergraduate Catalog of Studies, 2022-2023

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    Quality of experience and access network traffic management of HTTP adaptive video streaming

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    The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.Die Doktorarbeit beschäftigt sich mit Quality of Experience (QoE) – der subjektiv empfundenen Dienstgüte – von adaptivem HTTP Videostreaming (HAS) und mit Verkehrsmanagement, das in Zugangsnetzwerken eingesetzt werden kann, um die QoE des adaptiven Videostreamings zu verbessern. Zuerst wurde der Einfluss von Adaptionsparameters und der Zeit pro Qualitätsstufe auf die QoE von adaptivem Videostreaming mittels subjektiver Crowdsourcingstudien untersucht. Die Ergebnisse wurden benutzt, um die QoE-optimale Adaptionsstrategie für gegebene Videos und Netzwerkbedingungen zu berechnen. Dies ermöglicht Dienstanbietern von Videostreaming verbesserte Adaptionsstrategien für adaptives Videostreaming zu entwerfen und zu benchmarken. Weiterhin untersuchte die Arbeit Konzepte zum Überwachen von QoE von Videostreaming in der Applikation und im Netzwerk, die von Netzwerkbetreibern im Kreislauf des QoE-bewussten Verkehrsmanagements eingesetzt werden können. Außerdem wurde eine analytische und simulative Leistungsbewertung von QoE-bewusstem Verkehrsmanagement auf einer Engpassverbindung durchgeführt. Schließlich untersuchte diese Arbeit sozialbewusstes Verkehrsmanagement für adaptives Videostreaming mittels WLAN Offloading, also dem Auslagern von mobilen Videoflüssen über WLAN Netzwerke. Es wurde ein Modell für die Verteilung von öffentlichen WLAN Zugangspunkte und eine Plattform für sozialbewusstes Verkehrsmanagement auf privaten, häuslichen WLAN Routern vorgestellt. Abschließend untersuchte eine simulative Leistungsbewertung den Einfluss von WLAN Offloading auf die QoE und den Energieverbrauch von mobilem adaptivem Videostreaming

    Deteção de intrusões de rede baseada em anomalias

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    Dissertação de mestrado integrado em Eletrónica Industrial e ComputadoresAo longo dos últimos anos, a segurança de hardware e software tornou-se uma grande preocupação. À medida que a complexidade dos sistemas aumenta, as suas vulnerabilidades a sofisticadas técnicas de ataque têm proporcionalmente escalado. Frequentemente o problema reside na heterogenidade de dispositivos conectados ao veículo, tornando difícil a convergência da monitorização de todos os protocolos num único produto de segurança. Por esse motivo, o mercado requer ferramentas mais avançadas para a monitorizar ambientes críticos à vida humana, tais como os nossos automóveis. Considerando que existem várias formas de interagir com os sistemas de entretenimento do automóvel como o Bluetooth, o Wi-fi ou CDs multimédia, a necessidade de auditar as suas interfaces tornou-se uma prioridade, uma vez que elas representam um sério meio de aceeso à rede interna do carro. Atualmente, os mecanismos de segurança de um carro focam-se na monitotização da rede CAN, deixando para trás as tecnologias referidas e não contemplando os sistemas não críticos. Como exemplo disso, o Bluetooth traz desafios diferentes da rede CAN, uma vez que interage diretamente com o utilizador e está exposto a ataques externos. Uma abordagem alternativa para tornar o automóvel num sistema mais robusto é manter sob supervisão as comunicações que com este são estabelecidas. Ao implementar uma detecção de intrusão baseada em anomalias, esta dissertação visa analisar o protocolo Bluetooth no sentido de identificar interações anormais que possam alertar para uma situação fora dos padrões de utilização. Em última análise, este produto de software embebido incorpora uma grande margem de auto-aprendizagem, que é vital para enfrentar quaisquer ameaças desconhecidas e aumentar os níveis de segurança globais. Ao longo deste documento, apresentamos o estudo do problema seguido de uma metodologia alternativa que implementa um algoritmo baseado numa LSTM para prever a sequência de comandos HCI correspondentes a tráfego Bluetooth normal. Os resultados mostram a forma como esta abordagem pode impactar a deteção de intrusões nestes ambientes ao demonstrar uma grande capacidade para identificar padrões anómalos no conjunto de dados considerado.In the last few years, hardware and software security have become a major concern. As the systems’ complexity increases, its vulnerabilities to several sophisticated attack techniques have escalated likewise. Quite often, the problem lies in the heterogeneity of the devices connected to the vehicle, making it difficult to converge the monitoring systems of all existing protocols into one security product. Thereby, the market requires more refined tools to monitor life-risky environments such as personal vehicles. Considering that there are several ways to interact with the car’s infotainment system, such as Wi-fi, Bluetooth, or CD player, the need to audit these interfaces has become a priority as they represent a serious channel to reach the internal car network. Nowadays, security in car networks focuses on CAN bus monitoring, leaving behind the aforementioned technologies and not contemplating other non-critical systems. As an example of these concerns, Bluetooth brings different challenges compared to CAN as it interacts directly with the user, being exposed to external attacks. An alternative approach to converting modern vehicles and their set of computers into more robust systems is to keep track of established communications with them. By enforcing anomaly-based intrusion detection this dissertation aims to analyze the Bluetooth protocol to identify abnormal user interactions that may alert for a non conforming pattern. Ultimately, such embedded software product incorporates a self-learning edge, which is vital to face newly developed threats and increasing global security levels. Throughout this document, we present the study case followed by an alternative methodology that implements an LSTM based algorithm to predict a sequence of HCI commands corresponding to normal Bluetooth traffic. The results show how this approach can impact intrusion detection in such environments by expressing a high capability of identifying abnormal patterns in the considered data

    Physical sketching tools and techniques for customized sensate surfaces

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    Sensate surfaces are a promising avenue for enhancing human interaction with digital systems due to their inherent intuitiveness and natural user interface. Recent technological advancements have enabled sensate surfaces to surpass the constraints of conventional touchscreens by integrating them into everyday objects, creating interactive interfaces that can detect various inputs such as touch, pressure, and gestures. This allows for more natural and intuitive control of digital systems. However, prototyping interactive surfaces that are customized to users' requirements using conventional techniques remains technically challenging due to limitations in accommodating complex geometric shapes and varying sizes. Furthermore, it is crucial to consider the context in which customized surfaces are utilized, as relocating them to fabrication labs may lead to the loss of their original design context. Additionally, prototyping high-resolution sensate surfaces presents challenges due to the complex signal processing requirements involved. This thesis investigates the design and fabrication of customized sensate surfaces that meet the diverse requirements of different users and contexts. The research aims to develop novel tools and techniques that overcome the technical limitations of current methods and enable the creation of sensate surfaces that enhance human interaction with digital systems.Sensorische Oberflächen sind aufgrund ihrer inhärenten Intuitivität und natürlichen Benutzeroberfläche ein vielversprechender Ansatz, um die menschliche Interaktionmit digitalen Systemen zu verbessern. Die jüngsten technologischen Fortschritte haben es ermöglicht, dass sensorische Oberflächen die Beschränkungen herkömmlicher Touchscreens überwinden, indem sie in Alltagsgegenstände integriert werden und interaktive Schnittstellen schaffen, die diverse Eingaben wie Berührung, Druck, oder Gesten erkennen können. Dies ermöglicht eine natürlichere und intuitivere Steuerung von digitalen Systemen. Das Prototyping interaktiver Oberflächen, die mit herkömmlichen Techniken an die Bedürfnisse der Nutzer angepasst werden, bleibt jedoch eine technische Herausforderung, da komplexe geometrische Formen und variierende Größen nur begrenzt berücksichtigt werden können. Darüber hinaus ist es von entscheidender Bedeutung, den Kontext, in dem diese individuell angepassten Oberflächen verwendet werden, zu berücksichtigen, da eine Verlagerung in Fabrikations-Laboratorien zum Verlust ihres ursprünglichen Designkontextes führen kann. Zudem stellt das Prototyping hochauflösender sensorischer Oberflächen aufgrund der komplexen Anforderungen an die Signalverarbeitung eine Herausforderung dar. Diese Arbeit erforscht dasDesign und die Fabrikation individuell angepasster sensorischer Oberflächen, die den diversen Anforderungen unterschiedlicher Nutzer und Kontexte gerecht werden. Die Forschung zielt darauf ab, neuartigeWerkzeuge und Techniken zu entwickeln, die die technischen Beschränkungen derzeitigerMethoden überwinden und die Erstellung von sensorischen Oberflächen ermöglichen, die die menschliche Interaktion mit digitalen Systemen verbessern
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