786 resultados para sicurezza IoT internet of things privacy etica


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With the rapid development of internet-of-things (IoT), face scrambling has been proposed for privacy protection during IoT-targeted image/video distribution. Consequently in these IoT applications, biometric verification needs to be carried out in the scrambled domain, presenting significant challenges in face recognition. Since face models become chaotic signals after scrambling/encryption, a typical solution is to utilize traditional data-driven face recognition algorithms. While chaotic pattern recognition is still a challenging task, in this paper we propose a new ensemble approach – Many-Kernel Random Discriminant Analysis (MK-RDA) to discover discriminative patterns from chaotic signals. We also incorporate a salience-aware strategy into the proposed ensemble method to handle chaotic facial patterns in the scrambled domain, where random selections of features are made on semantic components via salience modelling. In our experiments, the proposed MK-RDA was tested rigorously on three human face datasets: the ORL face dataset, the PIE face dataset and the PUBFIG wild face dataset. The experimental results successfully demonstrate that the proposed scheme can effectively handle chaotic signals and significantly improve the recognition accuracy, making our method a promising candidate for secure biometric verification in emerging IoT applications.

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As technology advances not only do new standards and programming styles appear but also some of the previously established ones gain relevance. In a new Internet paradigm where interconnection between small devices is key to the development of new businesses and scientific advancement there is the need to find simple solutions that anyone can implement in order to allow ideas to become more than that, ideas. Open-source software is still alive and well, especially in the area of the Internet of Things. This opens windows for many low capital entrepreneurs to experiment with their ideas and actually develop prototypes, which can help identify problems with a project or shine light on possible new features and interactions. As programming becomes more and more popular between people of fields not related to software there is the need for guidance in developing something other than basic algorithms, which is where this thesis comes in: A comprehensive document explaining the challenges and available choices of developing a sensor data and message delivery system, which scales well and implements the delivery of critical messages. Modularity and extensibility were also given much importance, making this an affordable tool for anyone that wants to build a sensor network of the kind.

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Obiettivo di questa tesi è l'analisi e l'approfondimento di una tecnologia di nuova generazione che prende il nome di iBeacon. Basata sulla localizzazione di prossimità (wireless) a bassi consumi energetici e sviluppata da Apple, l'iBeacon sfrutta il protocollo Bluetooth Low Energy con il quale riesce ad utilizzare al meglio l'energia, permettendo alle batterie dei dispositivi che lo implementano di durare molto più a lungo. In questa argomentazione, vengono elencate e descritte alcune tecniche di comunicazione wireless a medio-corto raggio (Wi-Fi, Infrarosso, RFID, NFC, Bluetooth, BLE), che utilizzano lo scambio di informazioni senza fili, descrivendone una breve storia, dalla loro evoluzione nel tempo e nei modi, ad alcune caratteristiche di utilizzo. L'argomentazione poi focalizzerà l'attenzione sui metodi di localizzazione utilizzati dall'iBeacon, fornendone le funzionalità e le caratteristiche principali di questa nuova tecnologia e discutendone i vantaggi, i limiti tecnologici e di sviluppo del protocollo, fino a delineare alcune soluzioni per quanto riguarda le soglie di sicurezza e di privacy. L'analisi poi confronterà l'iBeacon con i maggiori antagonisti che utilizzano questa tecnica di microgeolocalizzazione (NFC, EddyStone). Si cercherà inoltre di delineare in maniera più dettagliata le specifiche tecniche che costituiscono questa nuova tecnologia di prossimità, dal protocollo di comunicazione alla componentistica hardware. Successivamente verrà descritto come un dispositivo iOS si interfaccia con un iBeacon, delineandone le API e il setup e mostrando i diversi passaggi per la creazione di un prototipo di applicazione. Si cercherà infine di pianificare, progettare e costruire una rete con iBeacon. Come ultima analisi, si prenderà in esame la relazione tra l'iBeacon e l'Internet of Things (IoT), e gli sviluppi che potrà portare all'evoluzione del Marketing di Prossimità, mostrando un esempio concreto di utilizzo efficace di questa innovativa tecnologia (EXPO 2015).

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In Europe, roughly three regimes apply to the liability of Internet intermediaries for privacy violations conducted by users through their network. These are: the e-Commerce Directive, which, under certain conditions, excludes them from liability; the Data Protection Directive, which imposes a number of duties and responsibilities on providers processing personal data; and the freedom of expression, contained inter alia in the ECHR, which, under certain conditions, grants Internet providers several privileges and freedoms. Each doctrine has its own field of application, but they also have partial overlap. In practice, this creates legal inequality and uncertainty, especially with regard to providers that host online platforms and process User Generated Content.

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After years of deliberation, the EU commission sped up the reform process of a common EU digital policy considerably in 2015 by launching the EU digital single market strategy. In particular, two core initiatives of the strategy were agreed upon: General Data Protection Regulation and the Network and Information Security (NIS) Directive law texts. A new initiative was additionally launched addressing the role of online platforms. This paper focuses on the platform privacy rationale behind the data protection legislation, primarily based on the proposal for a new EU wide General Data Protection Regulation. We analyse the legislation rationale from an Information System perspective to understand the role user data plays in creating platforms that we identify as “processing silos”. Generative digital infrastructure theories are used to explain the innovative mechanisms that are thought to govern the notion of digitalization and successful business models that are affected by digitalization. We foresee continued judicial data protection challenges with the now proposed Regulation as the adoption of the “Internet of Things” continues. The findings of this paper illustrate that many of the existing issues can be addressed through legislation from a platform perspective. We conclude by proposing three modifications to the governing rationale, which would not only improve platform privacy for the data subject, but also entrepreneurial efforts in developing intelligent service platforms. The first modification is aimed at improving service differentiation on platforms by lessening the ability of incumbent global actors to lock-in the user base to their service/platform. The second modification posits limiting the current unwanted tracking ability of syndicates, by separation of authentication and data store services from any processing entity. Thirdly, we propose a change in terms of how security and data protection policies are reviewed, suggesting a third party auditing procedure.

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With the development of the Internet-of-Things, more and more IoT platforms come up with different structures and characteristics. Making balance of their advantages and disadvantages, we should choose the suitable platform in differ- ent scenarios. For this project, I make comparison of a cloud-based centralized platform, Microsoft Azure IoT hub and a fully distributed platform, Sensi- bleThings. Quantitative comparison is made for performance by 2 scenarios, messages sending speed adds up, devices lie in different location. General com- parison is made for security, utilization and the storage. Finally I draw the con- clusion that SensibleThings performs more stable when a lot of messages push- es to the platform. Microsoft Azure has better geographic expansion. For gener- al comparison, Microsoft Azure IoT hub has better security. The requirement of local device for Microsoft Azure IoT hub is lower than SensibleThings. The SensibleThings are open source and free while Microsoft Azure follow the con- cept “pay as you go” with many throttling limitations for different editions. Microsoft is more user-friendly.

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The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However, as a paradigm, it is susceptible to a range of significant intrusion threats. This paper presents a threat analysis of the IoT and uses an Artificial Neural Network (ANN) to combat these threats. A multi-level perceptron, a type of supervised ANN, is trained using internet packet traces, then is assessed on its ability to thwart Distributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the classification of normal and threat patterns on an IoT Network. The ANN procedure is validated against a simulated IoT network. The experimental results demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS attacks.

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Only recently, during the past five years, consumer electronics has been evolving rapidly. Many products have started to include “smart home” capabilities, enabling communication and interoperability of various smart devices. Even more devices and sensors can be remote controlled and monitored through cloud services. While the smart home systems have become very affordable to average consumer compared to the early solutions decades ago, there are still many issues and things that need to be fixed or improved upon: energy efficiency, connectivity with other devices and applications, security and privacy concerns, reliability, and response time. This paper focuses on designing Internet of Things (IoT) node and platform architectures that take these issues into account, notes other currently used solutions, and selects technologies in order to provide better solution. The node architecture aims for energy efficiency and modularity, while the platform architecture goals are in scalability, portability, maintainability, performance, and modularity. Moreover, the platform architecture attempts to improve user experience by providing higher reliability and lower response time compared to the alternative platforms. The architectures were developed iteratively using a development process involving research, planning, design, implementation, testing, and analysis. Additionally, they were documented using Kruchten’s 4+1 view model, which is used to describe the use cases and different views of the architectures. The node architecture consisted of energy efficient hardware, FC3180 microprocessor and CC2520 RF transceiver, modular operating system, Contiki, and a communication protocol, AllJoyn, used for providing better interoperability with other IoT devices and applications. The platform architecture provided reliable low response time control, monitoring, and initial setup capabilities by utilizing web technologies on various devices such as smart phones, tablets, and computers. Furthermore, an optional cloud service was provided in order to control devices and monitor sensors remotely by utilizing scalable high performance technologies in the backend enabling low response time and high reliability.

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The continuous flow of technological developments in communications and electronic industries has led to the growing expansion of the Internet of Things (IoT). By leveraging the capabilities of smart networked devices and integrating them into existing industrial, leisure and communication applications, the IoT is expected to positively impact both economy and society, reducing the gap between the physical and digital worlds. Therefore, several efforts have been dedicated to the development of networking solutions addressing the diversity of challenges associated with such a vision. In this context, the integration of Information Centric Networking (ICN) concepts into the core of IoT is a research area gaining momentum and involving both research and industry actors. The massive amount of heterogeneous devices, as well as the data they produce, is a significant challenge for a wide-scale adoption of the IoT. In this paper we propose a service discovery mechanism, based on Named Data Networking (NDN), that leverages the use of a semantic matching mechanism for achieving a flexible discovery process. The development of appropriate service discovery mechanisms enriched with semantic capabilities for understanding and processing context information is a key feature for turning raw data into useful knowledge and ensuring the interoperability among different devices and applications. We assessed the performance of our solution through the implementation and deployment of a proof-of-concept prototype. Obtained results illustrate the potential of integrating semantic and ICN mechanisms to enable a flexible service discovery in IoT scenarios.

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This paper is an overview of some of the implications of IoT on the healthcare field. Due to the increasing of IoT solutions, healthcare cannot be outside of this paradigm. The contribution of this paper is to introduce directions to achieve a global connectivity between the Internet of Things (IoT) and the medical environments. The need to integrate all in a global environment is a huge challenge to all (from electrical engineers to data engineers).This revolution is redesigning the way we see healthcare, from the smallest sensor to the big data collected.

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The aim of this research was to identify the role of brand reputation in encouraging consumer willingness to provide personal data online, for the benefits of personalisation. This study extends on Malhotra, Kim and Agarwal’s (2004) Internet Users Information Privacy Concerns Model, and uses the theoretical underpinning of Social Contract Theory to assess how brand reputation moderates the relationship between trusting beliefs and perceived value (Privacy Calculus framework) with willingness to give personal information. The research is highly relevant as most privacy research undertaken to date focuses on consumer related concerns. Very little research exists examining the role of brand reputation and online privacy. Practical implications of this research include gaining knowledge as to how to minimise online privacy concerns; improve brand reputation; and provide insight on how to reduce consumer resistance to the collection of personal information and encourage consumer opt-in.

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A evolução constante em novas tecnologias que providenciam suporte à forma como os nossos dispositivos se ligam, bem como a forma como utilizamos diferentes capacidades e serviços on-line, criou um conjunto sem precedentes de novos desafios que motivam o desenvolvimento de uma recente área de investigação, denominada de Internet Futura. Nesta nova área de investigação, novos aspectos arquiteturais estão ser desenvolvidos, os quais, através da re-estruturação de componentes nucleares subjacentesa que compõem a Internet, progride-a de uma forma capaz de não são fazer face a estes novos desafios, mas também de a preparar para os desafios de amanhã. Aspectos chave pertencendo a este conjunto de desafios são os ambientes de rede heterogéneos compostos por diferentes tipos de redes de acesso, a cada vez maior mudança do tráfego peer-to-peer (P2P) como o tipo de tráfego mais utilizado na Internet, a orquestração de cenários da Internet das Coisas (IoT) que exploram mecanismos de interação Maquinaa-Maquina (M2M), e a utilização de mechanismos centrados na informação (ICN). Esta tese apresenta uma nova arquitetura capaz de simultaneamente fazer face a estes desafios, evoluindo os procedimentos de conectividade e entidades envolvidas, através da adição de uma camada de middleware, que age como um mecanismo de gestão de controlo avançado. Este mecanismo de gestão de controlo aproxima as entidades de alto nível (tais como serviços, aplicações, entidades de gestão de mobilidade, operações de encaminhamento, etc.) com as componentes das camadas de baixo nível (por exemplo, camadas de ligação, sensores e atuadores), permitindo uma otimização conjunta dos procedimentos de ligação subjacentes. Os resultados obtidos não só sublinham a flexibilidade dos mecanismos que compoem a arquitetura, mas também a sua capacidade de providenciar aumentos de performance quando comparados com outras soluÇÕes de funcionamento especÍfico, enquanto permite um maior leque de cenáios e aplicações.

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The broad capabilities of current mobile devices have paved the way for Mobile Crowd Sensing (MCS) applications. The success of this emerging paradigm strongly depends on the quality of received data which, in turn, is contingent to mass user participation; the broader the participation, the more useful these systems become. However, there is an ongoing trend that tries to integrate MCS applications with emerging computing paradigms such as cloud computing. The intuition is that such a transition can significantly improve the overall efficiency while at the same time it offers stronger security and privacy-preserving mechanisms for the end-user. In this position paper, we dwell on the underpinnings of incorporating cloud computing techniques to facilitate the vast amount of data collected in MCS applications. That is, we present a list of core system, security and privacy requirements that must be met if such a transition is to be successful. To this end, we first address several competing challenges not previously considered in the literature such as the scarce energy resources of battery-powered mobile devices as well as their limited computational resources that they often prevent the use of computationally heavy cryptographic operations and thus offering limited security services to the end-user. Finally, we present a use case scenario as a comprehensive example. Based on our findings, we posit open issues and challenges, and discuss possible ways to address them, so that security and privacy do not hinder the migration of MCS systems to the cloud.

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A Internet das Coisas tal como o Big Data e a análise dos dados são dos temas mais discutidos ao querermos observar ou prever as tendências do mercado para as próximas décadas, como o volume económico, financeiro e social, pelo que será relevante perceber a importância destes temas na atualidade. Nesta dissertação será descrita a origem da Internet das Coisas, a sua definição (por vezes confundida com o termo Machine to Machine, redes interligadas de máquinas controladas e monitorizadas remotamente e que possibilitam a troca de dados (Bahga e Madisetti 2014)), o seu ecossistema que envolve a tecnologia, software, dispositivos, aplicações, a infra-estrutura envolvente, e ainda os aspetos relacionados com a segurança, privacidade e modelos de negócios da Internet das Coisas. Pretende-se igualmente explicar cada um dos “Vs” associados ao Big Data: Velocidade, Volume, Variedade e Veracidade, a importância da Business Inteligence e do Data Mining, destacando-se algumas técnicas utilizadas de modo a transformar o volume dos dados em conhecimento para as empresas. Um dos objetivos deste trabalho é a análise das áreas de IoT, modelos de negócio e as implicações do Big Data e da análise de dados como elementos chave para a dinamização do negócio de uma empresa nesta área. O mercado da Internet of Things tem vindo a ganhar dimensão, fruto da Internet e da tecnologia. Devido à importância destes dois recursos e á falta de estudos em Portugal neste campo, com esta dissertação, sustentada na metodologia do “Estudo do Caso”, pretende-se dar a conhecer a experiência portuguesa no mercado da Internet das Coisas. Visa-se assim perceber quais os mecanismos utilizados para trabalhar os dados, a metodologia, sua importância, que consequências trazem para o modelo de negócio e quais as decisões tomadas com base nesses mesmos dados. Este estudo tem ainda como objetivo incentivar empresas portuguesas que estejam neste mercado ou que nele pretendam aceder, a adoptarem estratégias, mecanismos e ferramentas concretas no que diz respeito ao Big Data e análise dos dados.

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L’utilisation d’Internet prend beaucoup d’ampleur depuis quelques années et le commerce électronique connaît une hausse considérable. Nous pouvons présentement acheter facilement via Internet sans quitter notre domicile et avons accès à d’innombrables sources d’information. Cependant, la navigation sur Internet permet également la création de bases de données détaillées décrivant les habitudes de chaque utilisateur, informations ensuite utilisées par des tiers afin de cerner le profil de leur clientèle cible, ce qui inquiète plusieurs intervenants. Les informations concernant un individu peuvent être récoltées par l’interception de données transactionnelles, par l’espionnage en ligne, ainsi que par l’enregistrement d’adresses IP. Afin de résoudre les problèmes de vie privée et de s’assurer que les commerçants respectent la législation applicable en la matière, ainsi que les exigences mises de l’avant par la Commission européenne, plusieurs entreprises comme Zero-knowledge Systems Inc. et Anonymizer.com offrent des logiciels permettant la protection de la vie privée en ligne (privacy-enhancing technologies ou PETs). Ces programmes utilisent le cryptage d’information, une méthode rendant les données illisibles pour tous à l’exception du destinataire. L’objectif de la technologie utilisée a été de créer des systèmes mathématiques rigoureux pouvant empêcher la découverte de l’identité de l’auteur même par le plus déterminé des pirates, diminuant ainsi les risques de vol d’information ou la divulgation accidentelle de données confidentielles. Malgré le fait que ces logiciels de protection de la vie privée permettent un plus grand respect des Directives européennes en la matière, une analyse plus approfondie du sujet témoigne du fait que ces technologies pourraient être contraires aux lois concernant le cryptage en droit canadien, américain et français.