1,587 research outputs found
Towards Mobility Data Science (Vision Paper)
Mobility data captures the locations of moving objects such as humans,
animals, and cars. With the availability of GPS-equipped mobile devices and
other inexpensive location-tracking technologies, mobility data is collected
ubiquitously. In recent years, the use of mobility data has demonstrated
significant impact in various domains including traffic management, urban
planning, and health sciences. In this paper, we present the emerging domain of
mobility data science. Towards a unified approach to mobility data science, we
envision a pipeline having the following components: mobility data collection,
cleaning, analysis, management, and privacy. For each of these components, we
explain how mobility data science differs from general data science, we survey
the current state of the art and describe open challenges for the research
community in the coming years.Comment: Updated arXiv metadata to include two authors that were missing from
the metadata. PDF has not been change
Mapping the Current Landscape of Research Library Engagement with Emerging Technologies in Research and Learning: Final Report
The generation, dissemination, and analysis of digital information is a significant driver, and consequence, of technological change. As data and information stewards in physical and virtual space, research libraries are thoroughly entangled in the challenges presented by the Fourth Industrial Revolution:1 a societal shift powered not by steam or electricity, but by data, and characterized by a fusion of the physical and digital worlds.2 Organizing, structuring, preserving, and providing access to growing volumes of the digital data generated and required by research and industry will become a critically important function. As partners with the community of researchers and scholars, research libraries are also recognizing and adapting to the consequences of technological change in the practices of scholarship and scholarly communication. Technologies that have emerged or become ubiquitous within the last decade have accelerated information production and have catalyzed profound changes in the ways scholars, students, and the general public create and engage with information. The production of an unprecedented volume and diversity of digital artifacts, the proliferation of machine learning (ML) technologies,3 and the emergence of data as the “world’s most valuable resource,”4 among other trends, present compelling opportunities for research libraries to contribute in new and significant ways to the research and learning enterprise. Librarians are all too familiar with predictions of the research library’s demise in an era when researchers have so much information at their fingertips. A growing body of evidence provides a resounding counterpoint: that the skills, experience, and values of librarians, and the persistence of libraries as an institution, will become more important than ever as researchers contend with the data deluge and the ephemerality and fragility of much digital content. This report identifies strategic opportunities for research libraries to adopt and engage with emerging technologies,5 with a roughly fiveyear time horizon. It considers the ways in which research library values and professional expertise inform and shape this engagement, the ways library and library worker roles will be reconceptualized, and the implication of a range of technologies on how the library fulfills its mission. The report builds on a literature review covering the last five years of published scholarship, primarily North American information science literature, and interviews with a dozen library field experts, completed in fall 2019. It begins with a discussion of four cross-cutting opportunities that permeate many or all aspects of research library services. Next, specific opportunities are identified in each of five core research library service areas: facilitating information discovery, stewarding the scholarly and cultural record, advancing digital scholarship, furthering student learning and success, and creating learning and collaboration spaces. Each section identifies key technologies shaping user behaviors and library services, and highlights exemplary initiatives. Underlying much of the discussion in this report is the idea that “digital transformation is increasingly about change management”6 —that adoption of or engagement with emerging technologies must be part of a broader strategy for organizational change, for “moving emerging work from the periphery to the core,”7 and a broader shift in conceptualizing the research library and its services. Above all, libraries are benefitting from the ways in which emerging technologies offer opportunities to center users and move from a centralized and often siloed service model to embedded, collaborative engagement with the research and learning enterprise
Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets
This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade
A Framework for Preserving Privacy and Cybersecurity in Brain-Computer Interfacing Applications
Brain-Computer Interfaces (BCIs) comprise a rapidly evolving field of
technology with the potential of far-reaching impact in domains ranging from
medical over industrial to artistic, gaming, and military. Today, these
emerging BCI applications are typically still at early technology readiness
levels, but because BCIs create novel, technical communication channels for the
human brain, they have raised privacy and security concerns. To mitigate such
risks, a large body of countermeasures has been proposed in the literature, but
a general framework is lacking which would describe how privacy and security of
BCI applications can be protected by design, i.e., already as an integral part
of the early BCI design process, in a systematic manner, and allowing suitable
depth of analysis for different contexts such as commercial BCI product
development vs. academic research and lab prototypes. Here we propose the
adoption of recent systems-engineering methodologies for privacy threat
modeling, risk assessment, and privacy engineering to the BCI field. These
methodologies address privacy and security concerns in a more systematic and
holistic way than previous approaches, and provide reusable patterns on how to
move from principles to actions. We apply these methodologies to BCI and data
flows and derive a generic, extensible, and actionable framework for
brain-privacy-preserving cybersecurity in BCI applications. This framework is
designed for flexible application to the wide range of current and future BCI
applications. We also propose a range of novel privacy-by-design features for
BCIs, with an emphasis on features promoting BCI transparency as a prerequisite
for informational self-determination of BCI users, as well as design features
for ensuring BCI user autonomy. We anticipate that our framework will
contribute to the development of privacy-respecting, trustworthy BCI
technologies
Contributions to Context-Aware Smart Healthcare: A Security and Privacy Perspective
Les tecnologies de la informaciĂł i la comunicaciĂł han canviat les nostres vides de manera irreversible. La indĂşstria sanitĂ ria, una de les indĂşstries mĂ©s grans i de major creixement, estĂ dedicant molts esforços per adoptar les Ăşltimes tecnologies en la prĂ ctica mèdica diĂ ria. Per tant, no Ă©s sorprenent que els paradigmes sanitaris estiguin en constant evoluciĂł cercant serveis mĂ©s eficients, eficaços i sostenibles. En aquest context, el potencial de la computaciĂł ubiqua mitjançant telèfons intel·ligents, rellotges intel·ligents i altres dispositius IoT ha esdevingut fonamental per recopilar grans volums de dades, especialment relacionats amb l'estat de salut i la ubicaciĂł de les persones. Les millores en les capacitats de detecciĂł juntament amb l'apariciĂł de xarxes de telecomunicacions d'alta velocitat han facilitat la implementaciĂł d'entorns sensibles al context, com les cases i les ciutats intel·ligents, capaços d'adaptar-se a les necessitats dels ciutadans. La interacciĂł entre la computaciĂł ubiqua i els entorns sensibles al context va obrir la porta al paradigma de la salut intel·ligent, centrat en la prestaciĂł de serveis de salut personalitzats i de valor afegit mitjançant l'explotaciĂł de grans quantitats de dades sanitĂ ries, de mobilitat i contextuals. No obstant, la gestiĂł de dades sanitĂ ries, des de la seva recollida fins a la seva anĂ lisi, planteja una sèrie de problemes desafiants a causa del seu carĂ cter altament confidencial. Aquesta tesi tĂ© per objectiu abordar diversos reptes de seguretat i privadesa dins del paradigma de la salut intel·ligent. Els resultats d'aquesta tesi pretenen ajudar a la comunitat cientĂfica a millorar la seguretat dels entorns intel·ligents del futur, aixĂ com la privadesa dels ciutadans respecte a les seves dades personals i sanitĂ ries.Las tecnologĂas de la informaciĂłn y la comunicaciĂłn han cambiado nuestras vidas de forma irreversible. La industria sanitaria, una de las industrias más grandes y de mayor crecimiento, está dedicando muchos esfuerzos por adoptar las Ăşltimas tecnologĂas en la práctica mĂ©dica diaria. Por tanto, no es sorprendente que los paradigmas sanitarios estĂ©n en constante evoluciĂłn en busca de servicios más eficientes, eficaces y sostenibles. En este contexto, el potencial de la computaciĂłn ubicua mediante telĂ©fonos inteligentes, relojes inteligentes, dispositivos wearables y otros dispositivos IoT ha sido fundamental para recopilar grandes volĂşmenes de datos, especialmente relacionados con el estado de salud y la localizaciĂłn de las personas. Las mejoras en las capacidades de detecciĂłn junto con la apariciĂłn de redes de telecomunicaciones de alta velocidad han facilitado la implementaciĂłn de entornos sensibles al contexto, como las casas y las ciudades inteligentes, capaces de adaptarse a las necesidades de los ciudadanos. La interacciĂłn entre la computaciĂłn ubicua y los entornos sensibles al contexto abriĂł la puerta al paradigma de la salud inteligente, centrado en la prestaciĂłn de servicios de salud personalizados y de valor añadido mediante la explotaciĂłn significativa de grandes cantidades de datos sanitarios, de movilidad y contextuales. No obstante, la gestiĂłn de datos sanitarios, desde su recogida hasta su análisis, plantea una serie de cuestiones desafiantes debido a su naturaleza altamente confidencial. Esta tesis tiene por objetivo abordar varios retos de seguridad y privacidad dentro del paradigma de la salud inteligente. Los resultados de esta tesis pretenden ayudar a la comunidad cientĂfica a mejorar la seguridad de los entornos inteligentes del futuro, asĂ como la privacidad de los ciudadanos con respecto a sus datos personales y sanitarios.Information and communication technologies have irreversibly changed our lives. The healthcare industry, one of the world’s largest and fastest-growing industries, is dedicating many efforts in adopting the latest technologies into daily medical practice. It is not therefore surprising that healthcare paradigms are constantly evolving seeking for more efficient, effective and sustainable services. In this context, the potential of ubiquitous computing through smartphones, smartwatches, wearables and IoT devices has become fundamental to collect large volumes of data, including people's health status and people’s location. The enhanced sensing capabilities together with the emergence of high-speed telecommunication networks have facilitated the implementation of context-aware environments, such as smart homes and smart cities, able to adapt themselves to the citizens needs. The interplay between ubiquitous computing and context-aware environments opened the door to the so-called smart health paradigm, focused on the provision of added-value personalised health services by meaningfully exploiting vast amounts of health, mobility and contextual data. However, the management of health data, from their gathering to their analysis, arises a number of challenging issues due to their highly confidential nature. In particular, this dissertation addresses several security and privacy challenges within the smart health paradigm. The results of this dissertation are intended to help the research community to enhance the security of the intelligent environments of the future as well as the privacy of the citizens regarding their personal and health data
Ami-deu : un cadre sémantique pour des applications adaptables dans des environnements intelligents
Cette thèse vise à étendre l’utilisation de l'Internet des objets (IdO) en facilitant le développement d’applications par des personnes non experts en développement logiciel. La thèse propose une nouvelle approche pour augmenter la sémantique des applications d’IdO et l’implication des experts du domaine dans le développement d’applications sensibles au contexte. Notre approche permet de gérer le contexte changeant de l’environnement et de générer des applications qui s’exécutent dans plusieurs environnements intelligents pour fournir des actions requises dans divers contextes. Notre approche est mise en œuvre dans un cadriciel (AmI-DEU) qui inclut les composants pour le développement d’applications IdO. AmI-DEU intègre les services d’environnement, favorise l’interaction de l’utilisateur et fournit les moyens de représenter le domaine d’application, le profil de l’utilisateur et les intentions de l’utilisateur. Le cadriciel permet la définition d’applications IoT avec une intention d’activité autodécrite qui contient les connaissances requises pour réaliser l’activité. Ensuite, le cadriciel génère Intention as a Context (IaaC), qui comprend une intention d’activité autodécrite avec des connaissances colligées à évaluer pour une meilleure adaptation dans des environnements intelligents.
La sémantique de l’AmI-DEU est basée sur celle du ContextAA (Context-Aware Agents) – une plateforme pour fournir une connaissance du contexte dans plusieurs environnements. Le cadriciel effectue une compilation des connaissances par des règles et l'appariement sémantique pour produire des applications IdO autonomes capables de s’exécuter en ContextAA. AmI- DEU inclut également un outil de développement visuel pour le développement et le déploiement rapide d'applications sur ContextAA. L'interface graphique d’AmI-DEU adopte la métaphore du flux avec des aides visuelles pour simplifier le développement d'applications en permettant des définitions de règles étape par étape. Dans le cadre de l’expérimentation, AmI-DEU comprend un banc d’essai pour le développement d’applications IdO. Les résultats expérimentaux montrent une optimisation sémantique potentielle des ressources pour les applications IoT dynamiques dans les maisons intelligentes et les villes intelligentes.
Notre approche favorise l'adoption de la technologie pour améliorer le bienêtre et la qualité de vie des personnes. Cette thèse se termine par des orientations de recherche que le cadriciel AmI-DEU dévoile pour réaliser des environnements intelligents omniprésents fournissant des adaptations appropriées pour soutenir les intentions des personnes.Abstract: This thesis aims at expanding the use of the Internet of Things (IoT) by facilitating the development of applications by people who are not experts in software development. The thesis proposes a new approach to augment IoT applications’ semantics and domain expert involvement in context-aware application development. Our approach enables us to manage the changing environment context and generate applications that run in multiple smart environments to provide required actions in diverse settings. Our approach is implemented in a framework (AmI-DEU) that includes the components for IoT application development. AmI- DEU integrates environment services, promotes end-user interaction, and provides the means to represent the application domain, end-user profile, and end-user intentions. The framework enables the definition of IoT applications with a self-described activity intention that contains the required knowledge to achieve the activity. Then, the framework generates Intention as a Context (IaaC), which includes a self-described activity intention with compiled knowledge to be assessed for augmented adaptations in smart environments. AmI-DEU framework semantics adopts ContextAA (Context-Aware Agents) – a platform to provide context-awareness in multiple environments. The framework performs a knowledge compilation by rules and semantic matching to produce autonomic IoT applications to run in ContextAA. AmI-DEU also includes a visual tool for quick application development and deployment to ContextAA. The AmI-DEU GUI adopts the flow metaphor with visual aids to simplify developing applications by allowing step-by-step rule definitions. As part of the experimentation, AmI-DEU includes a testbed for IoT application development. Experimental results show a potential semantic optimization for dynamic IoT applications in smart homes and smart cities. Our approach promotes technology adoption to improve people’s well-being and quality of life. This thesis concludes with research directions that the AmI-DEU framework uncovers to achieve pervasive smart environments providing suitable adaptations to support people’s intentions
Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets
This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade
Contributions to the privacy provisioning for federated identity management platforms
Identity information, personal data and user’s profiles are key assets for organizations
and companies by becoming the use of identity management (IdM) infrastructures a prerequisite
for most companies, since IdM systems allow them to perform their business
transactions by sharing information and customizing services for several purposes in more
efficient and effective ways.
Due to the importance of the identity management paradigm, a lot of work has been done
so far resulting in a set of standards and specifications. According to them, under the
umbrella of the IdM paradigm a person’s digital identity can be shared, linked and reused
across different domains by allowing users simple session management, etc. In this way,
users’ information is widely collected and distributed to offer new added value services
and to enhance availability. Whereas these new services have a positive impact on users’
life, they also bring privacy problems.
To manage users’ personal data, while protecting their privacy, IdM systems are the ideal
target where to deploy privacy solutions, since they handle users’ attribute exchange.
Nevertheless, current IdM models and specifications do not sufficiently address comprehensive
privacy mechanisms or guidelines, which enable users to better control over the
use, divulging and revocation of their online identities. These are essential aspects, specially
in sensitive environments where incorrect and unsecured management of user’s data
may lead to attacks, privacy breaches, identity misuse or frauds.
Nowadays there are several approaches to IdM that have benefits and shortcomings, from
the privacy perspective.
In this thesis, the main goal is contributing to the privacy provisioning for federated
identity management platforms. And for this purpose, we propose a generic architecture
that extends current federation IdM systems. We have mainly focused our contributions
on health care environments, given their particularly sensitive nature. The two main
pillars of the proposed architecture, are the introduction of a selective privacy-enhanced
user profile management model and flexibility in revocation consent by incorporating an
event-based hybrid IdM approach, which enables to replace time constraints and explicit
revocation by activating and deactivating authorization rights according to events. The
combination of both models enables to deal with both online and offline scenarios, as well
as to empower the user role, by letting her to bring together identity information from
different sources.
Regarding user’s consent revocation, we propose an implicit revocation consent mechanism
based on events, that empowers a new concept, the sleepyhead credentials, which
is issued only once and would be used any time. Moreover, we integrate this concept
in IdM systems supporting a delegation protocol and we contribute with the definition
of mathematical model to determine event arrivals to the IdM system and how they are
managed to the corresponding entities, as well as its integration with the most widely
deployed specification, i.e., Security Assertion Markup Language (SAML).
In regard to user profile management, we define a privacy-awareness user profile management
model to provide efficient selective information disclosure. With this contribution a
service provider would be able to accesses the specific personal information without being
able to inspect any other details and keeping user control of her data by controlling
who can access. The structure that we consider for the user profile storage is based on
extensions of Merkle trees allowing for hash combining that would minimize the need of
individual verification of elements along a path. An algorithm for sorting the tree as we
envision frequently accessed attributes to be closer to the root (minimizing the access’
time) is also provided.
Formal validation of the above mentioned ideas has been carried out through simulations
and the development of prototypes. Besides, dissemination activities were performed in
projects, journals and conferences.Programa Oficial de Doctorado en IngenierĂa TelemáticaPresidente: MarĂa Celeste Campo Vázquez.- Secretario: MarĂa Francisca Hinarejos Campos.- Vocal: Ă“scar Esparza MartĂ
ConfLab: A Rich Multimodal Multisensor Dataset of Free-Standing Social Interactions in the Wild
Recording the dynamics of unscripted human interactions in the wild is
challenging due to the delicate trade-offs between several factors: participant
privacy, ecological validity, data fidelity, and logistical overheads. To
address these, following a 'datasets for the community by the community' ethos,
we propose the Conference Living Lab (ConfLab): a new concept for multimodal
multisensor data collection of in-the-wild free-standing social conversations.
For the first instantiation of ConfLab described here, we organized a real-life
professional networking event at a major international conference. Involving 48
conference attendees, the dataset captures a diverse mix of status,
acquaintance, and networking motivations. Our capture setup improves upon the
data fidelity of prior in-the-wild datasets while retaining privacy
sensitivity: 8 videos (1920x1080, 60 fps) from a non-invasive overhead view,
and custom wearable sensors with onboard recording of body motion (full 9-axis
IMU), privacy-preserving low-frequency audio (1250 Hz), and Bluetooth-based
proximity. Additionally, we developed custom solutions for distributed hardware
synchronization at acquisition, and time-efficient continuous annotation of
body keypoints and actions at high sampling rates. Our benchmarks showcase some
of the open research tasks related to in-the-wild privacy-preserving social
data analysis: keypoints detection from overhead camera views, skeleton-based
no-audio speaker detection, and F-formation detection.Comment: v2 is the version submitted to Neurips 2022 Datasets and Benchmarks
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