8,473 research outputs found
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Towards a Security, Privacy, Dependability, Interoperability Framework for the Internet of Things
A popular application of ambient intelligence systems constitutes of assisting living services on smart buildings. As intelligence is imported in embedded equipment, the system becomes able to provide smart services (e.g. control lights, airconditioning, provide energy management services etc.). IoT is the main enabler of such environments. However, the interconnection of these cyber-physical systems and the processing of personal data raise serious security and privacy issues. In this paper we present a framework that can guarantee Security, Privacy, Dependability and Interoperability (SPDI) in IoT. Taking advantage of the underlying IoT deployment, the proposed framework not only implements the requested smart functionality but also provide modelling and administration that can guarantee those SPDI properties. Moreover, we provide an application example of the framework in a smart building scenario
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Pattern-driven security, privacy, dependability and interoperability management of iot environments
Achieving Security, Privacy, Dependability and Interoperability (SPDI) is of paramount importance for the ubiquitous deployment and impact maximization of Internet of Things (IoT) applications. Nevertheless, said requirements are not only difficult to achieve at system initialization, but also hard to prove and maintain at run-time. This paper highlights an approach to tackling the above challenges, through the definition of pattern language and a framework that can guarantee SPDI in IoT orchestrations. By integrating pattern reasoning engines at the various layers of the IoT infrastructure, and a machine-processable representation of said pattern through Drools rules, the proposed framework can provide ways to fulfill SPDI requirements at design time, and also provide the means to guarantee those SPDI properties and manage the orchestrations accordingly. Moreover, an application example of the framework is presented in an Industrial IoT monitoring environment
A gap analysis of Internet-of-Things platforms
We are experiencing an abundance of Internet-of-Things (IoT) middleware
solutions that provide connectivity for sensors and actuators to the Internet.
To gain a widespread adoption, these middleware solutions, referred to as
platforms, have to meet the expectations of different players in the IoT
ecosystem, including device providers, application developers, and end-users,
among others. In this article, we evaluate a representative sample of these
platforms, both proprietary and open-source, on the basis of their ability to
meet the expectations of different IoT users. The evaluation is thus more
focused on how ready and usable these platforms are for IoT ecosystem players,
rather than on the peculiarities of the underlying technological layers. The
evaluation is carried out as a gap analysis of the current IoT landscape with
respect to (i) the support for heterogeneous sensing and actuating
technologies, (ii) the data ownership and its implications for security and
privacy, (iii) data processing and data sharing capabilities, (iv) the support
offered to application developers, (v) the completeness of an IoT ecosystem,
and (vi) the availability of dedicated IoT marketplaces. The gap analysis aims
to highlight the deficiencies of today's solutions to improve their integration
to tomorrow's ecosystems. In order to strengthen the finding of our analysis,
we conducted a survey among the partners of the Finnish IoT program, counting
over 350 experts, to evaluate the most critical issues for the development of
future IoT platforms. Based on the results of our analysis and our survey, we
conclude this article with a list of recommendations for extending these IoT
platforms in order to fill in the gaps.Comment: 15 pages, 4 figures, 3 tables, Accepted for publication in Computer
Communications, special issue on the Internet of Things: Research challenges
and solution
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