916 research outputs found

    Multi-Factor Authentication: A Survey

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    Today, digitalization decisively penetrates all the sides of the modern society. One of the key enablers to maintain this process secure is authentication. It covers many different areas of a hyper-connected world, including online payments, communications, access right management, etc. This work sheds light on the evolution of authentication systems towards Multi-Factor Authentication (MFA) starting from Single-Factor Authentication (SFA) and through Two-Factor Authentication (2FA). Particularly, MFA is expected to be utilized for human-to-everything interactions by enabling fast, user-friendly, and reliable authentication when accessing a service. This paper surveys the already available and emerging sensors (factor providers) that allow for authenticating a user with the system directly or by involving the cloud. The corresponding challenges from the user as well as the service provider perspective are also reviewed. The MFA system based on reversed Lagrange polynomial within Shamir’s Secret Sharing (SSS) scheme is further proposed to enable more flexible authentication. This solution covers the cases of authenticating the user even if some of the factors are mismatched or absent. Our framework allows for qualifying the missing factors by authenticating the user without disclosing sensitive biometric data to the verification entity. Finally, a vision of the future trends in MFA is discussed.Peer reviewe

    Internet of Things Architectures for Enhanced Living Environments

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    Ambient Assisted Living (AAL) is an emerging multidisciplinary research area that aims to create an ecosystem of different types of sensors, computers, mobile devices, wireless networks, and software applications for enhanced living environments and occupational health. There are several challenges in the development and implementation of an effective AAL system, such as system architecture, human-computer interaction, ergonomics, usability, and accessibility. There are also social and ethical challenges, such as acceptance by seniors and the privacy and confidentiality that must be a requirement of AAL devices. It is also essential to ensure that technology does not replace human care and is used as a relevant complement. The Internet of Things (IoT) is a paradigm where objects are connected to the Internet and support sensing capabilities. IoT devices should be ubiquitous, recognize the context, and support intelligence capabilities closely related to AAL. Technological advances allow defining new advanced tools and platforms for real-time health monitoring and decision making in the treatment of various diseases. IoT is a suitable approach to building healthcare systems, and it provides a suitable platform for ubiquitous health services, using, for example, portable sensors to carry data to servers and smartphones for communication. Despite the potential of the IoT paradigm and technologies for healthcare systems, several challenges to be overcome still exist. The direction and impact of IoT in the economy are not clearly defined, and there are barriers to the immediate and ubiquitous adoption of IoT products, services, and solutions. Several sources of pollutants have a high impact on indoor living environments. Consequently, indoor air quality is recognized as a fundamental variable to be controlled for enhanced health and well-being. It is critical to note that typically most people occupy more than 90% of their time inside buildings, and poor indoor air quality negatively affects performance and productivity. Research initiatives are required to address air quality issues to adopt legislation and real-time inspection mechanisms to improve public health, not only to monitor public places, schools, and hospitals but also to increase the rigor of building rules. Therefore, it is necessary to use real-time monitoring systems for correct analysis of indoor air quality to ensure a healthy environment in at least public spaces. In most cases, simple interventions provided by homeowners can produce substantial positive impacts on indoor air quality, such as avoiding indoor smoking and the correct use of natural ventilation. An indoor air quality monitoring system helps the detection and improvement of air quality conditions. Local and distributed assessment of chemical concentrations is significant for safety (e.g., detection of gas leaks and monitoring of pollutants) as well as to control heating, ventilation, and HVAC systems to improve energy efficiency. Real-time indoor air quality monitoring provides reliable data for the correct control of building automation systems and should be assumed as a decision support platform on planning interventions for enhanced living environments. However, the monitoring systems currently available are expensive and only allow the collection of random samples that are not provided with time information. Most solutions on the market only allow data consulting limited to device memory and require procedures for downloading and manipulating data with specific software. In this way, the development of innovative environmental monitoring systems based on ubiquitous technologies that allow real-time analysis becomes essential. This thesis resulted in the design and development of IoT architectures using modular and scalable structures for air quality monitoring based on data collected from cost-effective sensors for enhanced living environments. The proposed architectures address several concepts, including acquisition, processing, storage, analysis, and visualization of data. These systems incorporate an alert management Framework that notifies the user in real-time in poor indoor air quality scenarios. The software Framework supports multiple alert methods, such as push notifications, SMS, and e-mail. The real-time notification system offers several advantages when the goal is to achieve effective changes for enhanced living environments. On the one hand, notification messages promote behavioral changes. These alerts allow the building manager to identify air quality problems and plan interventions to avoid unhealthy air quality scenarios. The proposed architectures incorporate mobile computing technologies such as mobile applications that provide ubiquitous air quality data consulting methods s. Also, the data is stored and can be shared with medical teams to support the diagnosis. The state-of-the-art analysis has resulted in a review article on technologies, applications, challenges, opportunities, open-source IoT platforms, and operating systems. This review was significant to define the IoT-based Framework for indoor air quality supervision. The research leads to the development and design of cost-effective solutions based on open-source technologies that support Wi-Fi communication and incorporate several advantages such as modularity, scalability, and easy installation. The results obtained are auspicious, representing a significant contribution to enhanced living environments and occupational health. Particulate matter (PM) is a complex mixture of solid and liquid particles of organic and inorganic substances suspended in the air. Moreover, it is considered the pollutant that affects more people. The most damaging particles to health are ≀PM10 (diameter 10 microns or less), which can penetrate and lodge deep within the lungs, contributing to the risk of developing cardiovascular and respiratory diseases as well as lung cancer. Taking into account the adverse health effects of PM exposure, an IoT architecture for automatic PM monitoring was proposed. The proposed architecture is a PM real-time monitoring system and a decision-making tool. The solution consists of a hardware prototype for data acquisition and a Web Framework developed in .NET for data consulting. This system is based on open-source and technologies, with several advantages compared to existing systems, such as modularity, scalability, low-cost and easy installation. The data is stored in a database developed in SQL SERVER using .NET Web services. The results show the ability of the system to analyze the indoor air quality in real-time and the potential of the Web Framework for the planning of interventions to ensure safe, healthy, and comfortable conditions. Associations of high concentrations of carbon dioxide (CO2) with low productivity at work and increased health problems are well documented. There is also a clear correlation between high levels of CO2 and high concentrations of pollutants in indoor air. There are sufficient reasons to monitor CO2 and provide real-time notifications to improve occupational health and provide a safe and healthy indoor living environment. Taking into account the significant influence of CO2 for enhanced living environments, a real-time IoT architecture for CO2 monitoring was proposed. CO2 was selected because it is easy to measure and is produced in quantity (by people and combustion equipment). It can be used as an indicator of other pollutants and, therefore, of air quality in general. The solution consists of a hardware prototype for data acquisition environment, a Web software, and a smartphone application for data consulting. The proposed architecture is based on open-source technologies, and the data is stored in a SQL SERVER database. The mobile Framework allows the user not only to consult the latest data collected but also to receive real-time notifications in poor indoor air quality scenarios, and to configure the alerts threshold levels. The results show that the mobile application not only provides easy access to real-time air quality data, but also allows the user to maintain parameter history and provide a history of changes. Consequently, this system allows the user to analyze in a precise and detailed manner the behavior of air quality. Finally, an air quality monitoring solution was implemented, consisting of a hardware prototype that incorporates only the MICS-6814 sensor as the detection unit. This system monitors various air quality parameters such as NH3 (ammonia), CO (carbon monoxide), NO2 (nitrogen dioxide), C3H8 (propane), C4H10 (butane), CH4 (methane), H2 (hydrogen) and C2H5OH (ethanol). The monitoring of the concentrations of these pollutants is essential to provide enhanced living environments. This solution is based on Cloud, and the collected data is sent to the ThingSpeak platform. The proposed Framework combines sensitivity, flexibility, and measurement accuracy in real-time, allowing a significant evolution of current air quality controls. The results show that this system provides easy, intuitive, and fast access to air quality data as well as relevant notifications in poor air quality situations to provide real-time intervention and improve occupational health. These data can be accessed by physicians to support diagnoses and correlate the symptoms and health problems of patients with the environment in which they live. As future work, the results reported in this thesis can be considered as a starting point for the development of a secure system sharing data with health professionals in order to serve as decision support in diagnosis.Ambient Assisted Living (AAL) Ă© uma ĂĄrea de investigação multidisciplinar emergente que visa a construção de um ecossistema de diferentes tipos de sensores, microcontroladores, dispositivos mĂłveis, redes sem fios e aplicaçÔes de software para melhorar os ambientes de vida e a saĂșde ocupacional. Existem muitos desafios no desenvolvimento e na implementação de um sistema AAL, como a arquitetura do sistema, interação humano-computador, ergonomia, usabilidade e acessibilidade. Existem tambĂ©m problemas sociais e Ă©ticos, como a aceitação por parte dos utilizadores mais vulnerĂĄveis e a privacidade e confidencialidade, que devem ser uma exigĂȘncia de todos os dispositivos AAL. De facto, tambĂ©m Ă© essencial assegurar que a tecnologia nĂŁo substitua o cuidado humano e seja usada como um complemento essencial. A Internet das Coisas (IoT) Ă© um paradigma em que os objetos estĂŁo conectados Ă  Internet e suportam recursos sensoriais. Tendencialmente, os dispositivos IoT devem ser omnipresentes, reconhecer o contexto e ativar os recursos de inteligĂȘncia ambiente intimamente relacionados ao AAL. Os avanços tecnolĂłgicos permitem definir novas ferramentas avançadas e plataformas para monitorização de saĂșde em tempo real e tomada de decisĂŁo no tratamento de vĂĄrias doenças. A IoT Ă© uma abordagem adequada para construir sistemas de saĂșde sendo que oferece uma plataforma para serviços de saĂșde ubĂ­quos, usando, por exemplo, sensores portĂĄteis para recolha e transmissĂŁo de dados e smartphones para comunicação. Apesar do potencial do paradigma e tecnologias IoT para o desenvolvimento de sistemas de saĂșde, muitos desafios continuam ainda por ser resolvidos. A direção e o impacto das soluçÔes IoT na economia nĂŁo estĂĄ claramente definido existindo, portanto, barreiras Ă  adoção imediata de produtos, serviços e soluçÔes de IoT. Os ambientes de vida sĂŁo caracterizados por diversas fontes de poluentes. Consequentemente, a qualidade do ar interior Ă© reconhecida como uma variĂĄvel fundamental a ser controlada de forma a melhorar a saĂșde e o bem-estar. É importante referir que tipicamente a maioria das pessoas ocupam mais de 90% do seu tempo no interior de edifĂ­cios e que a mĂĄ qualidade do ar interior afeta negativamente o desempenho e produtividade. É necessĂĄrio que as equipas de investigação continuem a abordar os problemas de qualidade do ar visando a adoção de legislação e mecanismos de inspeção que atuem em tempo real para a melhoraria da saĂșde e qualidade de vida, tanto em locais pĂșblicos como escolas e hospitais e residĂȘncias particulares de forma a aumentar o rigor das regras de construção de edifĂ­cios. Para tal, Ă© necessĂĄrio utilizar mecanismos de monitorização em tempo real de forma a possibilitar a anĂĄlise correta da qualidade do ambiente interior para garantir ambientes de vida saudĂĄveis. Na maioria dos casos, intervençÔes simples que podem ser executadas pelos proprietĂĄrios ou ocupantes da residĂȘncia podem produzir impactos positivos substanciais na qualidade do ar interior, como evitar fumar em ambientes fechados e o uso correto de ventilação natural. Um sistema de monitorização e avaliação da qualidade do ar interior ajuda na deteção e na melhoria das condiçÔes ambiente. A avaliação local e distribuĂ­da das concentraçÔes quĂ­micas Ă© significativa para a segurança (por exemplo, deteção de fugas de gĂĄs e supervisĂŁo dos poluentes) bem como para controlar o aquecimento, ventilação, e sistemas de ar condicionado (HVAC) visando a melhoria da eficiĂȘncia energĂ©tica. A monitorização em tempo real da qualidade do ar interior fornece dados fiĂĄveis para o correto controlo de sistemas de automação de edifĂ­cios e deve ser assumida com uma plataforma de apoio Ă  decisĂŁo no que se refere ao planeamento de intervençÔes para ambientes de vida melhorados. No entanto, os sistemas de monitorização atualmente disponĂ­veis sĂŁo de alto custo e apenas permitem a recolha de amostras aleatĂłrias que nĂŁo sĂŁo providas de informação temporal. A maioria das soluçÔes disponĂ­veis no mercado permite apenas a acesso ao histĂłrico de dados que Ă© limitado Ă  memĂłria do dispositivo e exige procedimentos de download e manipulação de dados com software proprietĂĄrio. Desta forma, o desenvolvimento de sistemas inovadores de monitorização ambiente baseados em tecnologias ubĂ­quas e computação mĂłvel que permitam a anĂĄlise em tempo real torna-se essencial. A Tese resultou na definição e no desenvolvimento de arquiteturas para monitorização da qualidade do ar baseadas em IoT. Os mĂ©todos propostos sĂŁo de baixo custo e recorrem a estruturas modulares e escalĂĄveis para proporcionar ambientes de vida melhorados. As arquiteturas propostas abordam vĂĄrios conceitos, incluindo aquisição, processamento, armazenamento, anĂĄlise e visualização de dados. Os mĂ©todos propostos incorporam Frameworks de gestĂŁo de alertas que notificam o utilizador em tempo real e de forma ubĂ­qua quando a qualidade do ar interior Ă© deficiente. A estrutura de software suporta vĂĄrios mĂ©todos de notificação, como notificaçÔes remotas para smartphone, SMS (Short Message Service) e email. O mĂ©todo usado para o envio de notificaçÔes em tempo real oferece vĂĄrias vantagens quando o objetivo Ă© alcançar mudanças efetivas para ambientes de vida melhorados. Por um lado, as mensagens de notificação promovem mudanças de comportamento. De facto, estes alertas permitem que o gestor do edifĂ­cio e os ocupantes reconheçam padrĂ”es da qualidade do ar e permitem tambĂ©m um correto planeamento de intervençÔes de forma evitar situaçÔes em que a qualidade do ar Ă© deficiente. Por outro lado, o sistema proposto incorpora tecnologias de computação mĂłvel, como aplicaçÔes mĂłveis, que fornecem acesso omnipresente aos dados de qualidade do ar e, consequentemente, fornecem soluçÔes completas para anĂĄlise de dados. AlĂ©m disso, os dados sĂŁo armazenados e podem ser partilhados com equipas mĂ©dicas para ajudar no diagnĂłstico. A anĂĄlise do estado da arte resultou na elaboração de um artigo de revisĂŁo sobre as tecnologias, aplicaçÔes, desafios, plataformas e sistemas operativos que envolvem a criação de arquiteturas IoT. Esta revisĂŁo foi um trabalho fundamental na definição das arquiteturas propostas baseado em IoT para a supervisĂŁo da qualidade do ar interior. Esta pesquisa conduz a um desenvolvimento de arquiteturas IoT de baixo custo com base em tecnologias de cĂłdigo aberto que operam como um sistema Wi-Fi e suportam vĂĄrias vantagens, como modularidade, escalabilidade e facilidade de instalação. Os resultados obtidos sĂŁo muito promissores, representando uma contribuição significativa para ambientes de vida melhorados e saĂșde ocupacional. O material particulado (PM) Ă© uma mistura complexa de partĂ­culas sĂłlidas e lĂ­quidas de substĂąncias orgĂąnicas e inorgĂąnicas suspensas no ar e Ă© considerado o poluente que afeta mais pessoas. As partĂ­culas mais prejudiciais Ă  saĂșde sĂŁo as ≀PM10 (diĂąmetro de 10 micrĂłmetros ou menos), que podem penetrar e fixarem-se dentro dos pulmĂ”es, contribuindo para o risco de desenvolver doenças cardiovasculares e respiratĂłrias, bem como de cancro do pulmĂŁo. Tendo em consideração os efeitos negativos para a saĂșde da exposição ao PM foi desenvolvido numa primeira fase uma arquitetura IoT para monitorização automĂĄtica dos nĂ­veis de PM. Esta arquitetura Ă© um sistema que permite monitorização de PM em tempo real e uma ferramenta de apoio Ă  tomada de decisĂŁo. A solução Ă© composta por um protĂłtipo de hardware para aquisição de dados e um portal Web desenvolvido em .NET para consulta de dados. Este sistema Ă© baseado em tecnologias de cĂłdigo aberto com vĂĄrias vantagens em comparação aos sistemas existentes, como modularidade, escalabilidade, baixo custo e fĂĄcil instalação. Os dados sĂŁo armazenados numa base de dados desenvolvida em SQL SERVER e sĂŁo enviados com recurso a serviços Web. Os resultados mostram a capacidade do sistema de analisar em tempo real a qualidade do ar interior e o potencial da Framework Web para o planeamento de intervençÔes com o objetivo de garantir condiçÔes seguras, saudĂĄveis e confortĂĄveis. AssociaçÔes de altas concentraçÔes de diĂłxido de carbono (CO2) com dĂ©fice de produtividade no trabalho e aumento de problemas de saĂșde encontram-se bem documentadas. Existe tambĂ©m uma correlação evidente entre altos nĂ­veis de CO2 e altas concentraçÔes de poluentes no ar interior. Tendo em conta a influĂȘncia significativa do CO2 para a construção de ambientes de vida melhorados desenvolveu-se uma solução de monitorização em tempo real de CO2 com base na arquitetura de IoT. A arquitetura proposta permite tambĂ©m o envio de notificaçÔes em tempo real para melhorar a saĂșde ocupacional e proporcionar um ambiente de vida interior seguro e saudĂĄvel. O CO2 foi selecionado, pois Ă© fĂĄcil de medir e Ă© produzido em quantidade (por pessoas e equipamentos de combustĂŁo). Assim, pode ser usado como um indicador de outros poluentes e, portanto, da qualidade do ar em geral. O mĂ©todo proposto Ă© composto por um protĂłtipo de hardware para aquisição de dados, um software Web e uma aplicação smartphone para consulta de dados. Esta arquitetura Ă© baseada em tecnologias de cĂłdigo aberto e os dados recolhidos sĂŁo armazenados numa base de dados SQL SERVER. A Framework mĂłvel permite nĂŁo sĂł consultar em tempo real os Ășltimos dados recolhidos, receber notificaçÔes com o objetivo de avisar o utilizador quando a qualidade do ar estĂĄ deficiente, mas tambĂ©m para configurar alertas. Os resultados mostram que a Framework mĂłvel fornece nĂŁo apenas acesso fĂĄcil aos dados da qualidade do ar em tempo real, mas tambĂ©m permite ao utilizador manter o histĂłrico de parĂąmetros. Assim este sistema permite ao utilizador analisar de maneira precisa e detalhada o comportamento da qualidade do ar interior. Por Ășltimo, Ă© proposta uma arquitetura para monitorização de vĂĄrios parĂąmetros da qualidade do ar, como NH3 (amonĂ­aco), CO (monĂłxido de carbono), NO2 (diĂłxido de azoto), C3H8 (propano), C4H10 (butano), CH4 (metano), H2 (hidrogĂ©nio) e C2H5OH (etanol). Esta arquitetura Ă© composta por um protĂłtipo de hardware que incorpora unicamente o sensor MICS-6814 como unidade de deteção. O controlo das concentraçÔes destes poluentes Ă© extremamente relevante para proporcionar ambientes de vida melhorados. Esta solução tem base na Cloud sendo que os dados recolhidos sĂŁo enviados para a plataforma ThingSpeak. Esta Framework combina sensibilidade, flexibilidade e precisĂŁo de medição em tempo real, permitindo uma evolução significativa dos atuais sistemas de monitorização da qualidade do ar. Os resultados mostram que este sistema fornece acesso fĂĄcil, intuitivo e rĂĄpido aos dados de qualidade do ar bem como notificaçÔes essenciais em situaçÔes de qualidade do ar deficiente de forma a planear intervençÔes em tempo Ăștil e melhorar a saĂșde ocupacional. Esses dados podem ser acedidos pelos mĂ©dicos para apoiar diagnĂłsticos e correlacionar os sintomas e problemas de saĂșde dos pacientes com o ambiente em que estes vivem. Como trabalho futuro, os resultados reportados nesta Tese podem ser considerados um ponto de partida para o desenvolvimento de um sistema seguro para partilha de dados com profissionais de saĂșde de forma a servir de suporte Ă  decisĂŁo no diagnĂłstico

    Smartphone: The Ultimate IoT and IoE Device

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    Internet of Things (IoT) and Internet of Everything (IoE) are emerging communication concepts that will interconnect a variety of devices (including smartphones, home appliances, sensors, and other network devices), people, data, and processes and allow them to communicate with each other seamlessly. These new concepts can be applied in many application domains such as healthcare, transportation, and supply chain management (SCM), to name a few, and allow users to get real-time information such as location-based services, disease management, and tracking. The smartphone-enabling technologies such as built-in sensors, Bluetooth, radio-frequency identification (RFID) tracking, and near-field communications (NFC) allow it to be an integral part of IoT and IoE world and the mostly used device in these environments. However, its use imposes severe security and privacy threats, because the smartphone usually contains and communicates sensitive private data. In this chapter, we provide a comprehensive survey on IoT and IoE technologies, their application domains, IoT structure and architecture, the use of smartphones in IoT and IoE, and the difference between IoT networks and mobile cellular networks. We also provide a concise overview of future opportunities and challenges in IoT and IoE environments and focus more on the security and privacy threats of using the smartphone in IoT and IoE networks with a suggestion of some countermeasures

    M-health review: joining up healthcare in a wireless world

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    In recent years, there has been a huge increase in the use of information and communication technologies (ICT) to deliver health and social care. This trend is bound to continue as providers (whether public or private) strive to deliver better care to more people under conditions of severe budgetary constraint

    Social, Private, and Trusted Wearable Technology under Cloud-Aided Intermittent Wireless Connectivity

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    There has been an unprecedented increase in the use of smart devices globally, together with novel forms of communication, computing, and control technologies that have paved the way for a new category of devices, known as high-end wearables. While massive deployments of these objects may improve the lives of people, unauthorized access to the said private equipment and its connectivity is potentially dangerous. Hence, communication enablers together with highly-secure human authentication mechanisms have to be designed.In addition, it is important to understand how human beings, as the primary users, interact with wearable devices on a day-to-day basis; usage should be comfortable, seamless, user-friendly, and mindful of urban dynamics. Usually the connectivity between wearables and the cloud is executed through the user’s more power independent gateway: this will usually be a smartphone, which may have potentially unreliable infrastructure connectivity. In response to these unique challenges, this thesis advocates for the adoption of direct, secure, proximity-based communication enablers enhanced with multi-factor authentication (hereafter refereed to MFA) that can integrate/interact with wearable technology. Their intelligent combination together with the connection establishment automation relying on the device/user social relations would allow to reliably grant or deny access in cases of both stable and intermittent connectivity to the trusted authority running in the cloud.The introduction will list the main communication paradigms, applications, conventional network architectures, and any relevant wearable-speciïŹc challenges. Next, the work examines the improved architecture and security enablers for clusterization between wearable gateways with a proximity-based communication as a baseline. Relying on this architecture, the author then elaborates on the social ties potentially overlaying the direct connectivity management in cases of both reliable and unreliable connection to the trusted cloud. The author discusses that social-aware cooperation and trust relations between users and/or the devices themselves are beneïŹcial for the architecture under proposal. Next, the author introduces a protocol suite that enables temporary delegation of personal device use dependent on diïŹ€erent connectivity conditions to the cloud.After these discussions, the wearable technology is analyzed as a biometric and behavior data provider for enabling MFA. The conventional approaches of the authentication factor combination strategies are compared with the ‘intelligent’ method proposed further. The assessment ïŹnds signiïŹcant advantages to the developed solution over existing ones.On the practical side, the performance evaluation of existing cryptographic primitives, as part of the experimental work, shows the possibility of developing the experimental methods further on modern wearable devices.In summary, the set of enablers developed here for wearable technology connectivity is aimed at enriching people’s everyday lives in a secure and usable way, in cases when communication to the cloud is not consistently available

    Usable privacy and security in smart homes

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    Ubiquitous computing devices increasingly dominate our everyday lives, including our most private places: our homes. Homes that are equipped with interconnected, context-aware computing devices, are considered “smart” homes. To provide their functionality and features, these devices are typically equipped with sensors and, thus, are capable of collecting, storing, and processing sensitive user data, such as presence in the home. At the same time, these devices are prone to novel threats, making our homes vulnerable by opening them for attackers from outside, but also from within the home. For instance, remote attackers who digitally gain access to presence data can plan for physical burglary. Attackers who are physically present with access to devices could access associated (sensitive) user data and exploit it for further cyberattacks. As such, users’ privacy and security are at risk in their homes. Even worse, many users are unaware of this and/or have limited means to take action. This raises the need to think about usable mechanisms that can support users in protecting their smart home setups. The design of such mechanisms, however, is challenging due to the variety and heterogeneity of devices available on the consumer market and the complex interplay of user roles within this context. This thesis contributes to usable privacy and security research in the context of smart homes by a) understanding users’ privacy perceptions and requirements for usable mechanisms and b) investigating concepts and prototypes for privacy and security mechanisms. Hereby, the focus is on two specific target groups, that are inhabitants and guests of smart homes. In particular, this thesis targets their awareness of potential privacy and security risks, enables them to take control over their personal privacy and security, and illustrates considerations for usable authentication mechanisms. This thesis provides valuable insights to help researchers and practitioners in designing and evaluating privacy and security mechanisms for future smart devices and homes, particularly targeting awareness, control, and authentication, as well as various roles.Computer und andere „intelligente“, vernetzte GerĂ€te sind allgegenwĂ€rtig und machen auch vor unserem privatesten Zufluchtsort keinen Halt: unserem Zuhause. Ein „intelligentes Heim“ verspricht viele Vorteile und nĂŒtzliche Funktionen. Um diese zu erfĂŒllen, sind die GerĂ€te mit diversen Sensoren ausgestattet – sie können also in unserem Zuhause sensitive Daten sammeln, speichern und verarbeiten (bspw. Anwesenheit). Gleichzeitig sind die GerĂ€te anfĂ€llig fĂŒr (neuartige) Cyberangriffe, gefĂ€hrden somit unser Zuhause und öffnen es fĂŒr potenzielle – interne sowie externe – Angreifer. Beispielsweise könnten Angreifer, die digital Zugriff auf sensitive Daten wie PrĂ€senz erhalten, einen physischen Überfall in Abwesenheit der Hausbewohner planen. Angreifer, die physischen Zugriff auf ein GerĂ€t erhalten, könnten auf assoziierte Daten und Accounts zugreifen und diese fĂŒr weitere Cyberangriffe ausnutzen. Damit werden die PrivatsphĂ€re und Sicherheit der Nutzenden in deren eigenem Zuhause gefĂ€hrdet. Erschwerend kommt hinzu, dass viele Nutzenden sich dessen nicht bewusst sind und/oder nur limitierte Möglichkeiten haben, effiziente Gegenmaßnahmen zu ergreifen. Dies macht es unabdingbar, ĂŒber benutzbare Mechanismen nachzudenken, die Nutzende beim Schutz ihres intelligenten Zuhauses unterstĂŒtzen. Die Umsetzung solcher Mechanismen ist allerdings eine große Herausforderung. Das liegt unter anderem an der großen Vielfalt erhĂ€ltlicher GerĂ€te von verschiedensten Herstellern, was das Finden einer einheitlichen Lösung erschwert. DarĂŒber hinaus interagieren im Heimkontext meist mehrere Nutzende in verschieden Rollen (bspw. Bewohner und GĂ€ste), was die Gestaltung von Mechanismen zusĂ€tzlich erschwert. Diese Doktorarbeit trĂ€gt dazu bei, benutzbare PrivatsphĂ€re- und Sicherheitsmechanismen im Kontext des „intelligenten Zuhauses“ zu entwickeln. Insbesondere werden a) die Wahrnehmung von PrivatsphĂ€re sowie Anforderungen an potenzielle Mechanismen untersucht, sowie b) Konzepte und Prototypen fĂŒr PrivatsphĂ€re- und Sicherheitsmechanismen vorgestellt. Der Fokus liegt hierbei auf zwei Zielgruppen, den Bewohnern sowie den GĂ€sten eines intelligenten Zuhauses. Insbesondere werden in dieser Arbeit deren Bewusstsein fĂŒr potenzielle PrivatsphĂ€re- und Sicherheits-Risiken adressiert, ihnen Kontrolle ĂŒber ihre persönliche PrivatsphĂ€re und Sicherheit ermöglicht, sowie Möglichkeiten fĂŒr benutzbare Authentifizierungsmechanismen fĂŒr beide Zielgruppen aufgezeigt. Die Ergebnisse dieser Doktorarbeit legen den Grundstein fĂŒr zukĂŒnftige Entwicklung und Evaluierung von benutzbaren PrivatsphĂ€re und Sicherheitsmechanismen im intelligenten Zuhause
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