940,452 research outputs found

    Governance and Policy Cooperation on the Cyber Security of the Internet of Things

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    This report was based on a workshop. The impetus for this workshop was the recognition that international policy cooperation on the cybersecurity aspects of the IoT has made little progress. This is due in part to a failure to establish a functioning community of technicians and policymakers who are jointly focusing on these issues. From a technical perspective, the IoT will significantly increase opportunities to breach security via new attack surfaces. For policymakers, the heightened insecurity created by the rapid expansion of the IoT marks a significant governance challenge. Addressing these security deficiencies will require an increase in the capacity to share threat information as well as a range of innovative technical and policy solutions. The workshop marked a starting point in building a global community of security practitioners and policymakers who are interested in these issues and who are working on similar topics

    The Internet of Hackable Things

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    The Internet of Things makes possible to connect each everyday object to the Internet, making computing pervasive like never before. From a security and privacy perspective, this tsunami of connectivity represents a disaster, which makes each object remotely hackable. We claim that, in order to tackle this issue, we need to address a new challenge in security: education

    eHealth and the Internet of Things

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    To respond to an ageing population, eHealth strategies offer significant opportunities in achieving a balanced and sustainable healthcare infrastructure. Advances in technology both at the sensor and device levels and in respect of information technology have opened up other possibilities and options. Of significance among these is what is increasingly referred to as the Internet of Things, the interconnection of physical devices to an information infrastructure. The paper therefore sets out to position the Internet of Things at the core of future developments in eHealt

    Digital Materiality of the Internet-of-Things

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    date-added: 2015-01-19 04:14:58 +0000 date-modified: 2015-04-01 06:51:10 +0000date-added: 2015-01-19 04:14:58 +0000 date-modified: 2015-04-01 06:51:10 +0000This work was supported by the Arts and Humanities Research Council, CreativeWorks London Hub, grant AH/J005142/1, and the European Regional Development Fund, London Creative and Digital Fusion

    A Semantic Collaboration Method Based on Uniform Knowledge Graph

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    The Semantic Internet of Things is the extension of the Internet of Things and the Semantic Web, which aims to build an interoperable collaborative system to solve the heterogeneous problems in the Internet of Things. However, the Semantic Internet of Things has the characteristics of both the Internet of Things and the Semantic Web environment, and the corresponding semantic data presents many new data features. In this study, we analyze the characteristics of semantic data and propose the concept of a uniform knowledge graph, allowing us to be applied to the environment of the Semantic Internet of Things better. Here, we design a semantic collaboration method based on a uniform knowledge graph. It can take the uniform knowledge graph as the form of knowledge organization and representation, and provide a useful data basis for semantic collaboration by constructing semantic links to complete semantic relation between different data sets, to achieve the semantic collaboration in the Semantic Internet of Things. Our experiments show that the proposed method can analyze and understand the semantics of user requirements better and provide more satisfactory outcomes

    A Middleware for the Internet of Things

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    The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as things to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things, or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.Comment: 20 pages, International Journal of Computer Networks & Communications (IJCNC) Vol.8, No.2, March 201

    Big Data and the Internet of Things

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    Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea
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