The diffusion of Internet of Things (IoT) technologies not only enables the provision of advanced and valuable services, but also raises several challenges. First of all, the increasing number of heterogeneous interconnected devices creates scalability and interoperability issues, and thus, a flexible middleware platform is needed to manage all the sources together with all the tasks related to data collection and integration. In fact, the large amount of data has to be properly managed. In particular, on the one hand, data have to be protected from security threats; on the other hand, it is necessary to consider that data are useful only if their quality is suitable for the processes in which they have to be used. For these reasons, it is important that applications/users that aim to exploit the collected data are aware of data quality and security levels in order to understand if data can be trusted and thus used. In this chapter, we present a distributed architecture for managing IoT data extraction and processing that also includes algorithms for the assessment of data quality and security levels of considered sources. A prototype of such an architecture has been realized; through a user interface, it is possible to access data services able to filter data from IoT devices on the basis of security and data quality requirements. The chapter describes the prototype and shows some experiments performed by using several real-time open data feeds characterized by different levels of reliability, quality and security.

Toward data governance in the internet of things

Cappiello, Cinzia;
2018

Abstract

The diffusion of Internet of Things (IoT) technologies not only enables the provision of advanced and valuable services, but also raises several challenges. First of all, the increasing number of heterogeneous interconnected devices creates scalability and interoperability issues, and thus, a flexible middleware platform is needed to manage all the sources together with all the tasks related to data collection and integration. In fact, the large amount of data has to be properly managed. In particular, on the one hand, data have to be protected from security threats; on the other hand, it is necessary to consider that data are useful only if their quality is suitable for the processes in which they have to be used. For these reasons, it is important that applications/users that aim to exploit the collected data are aware of data quality and security levels in order to understand if data can be trusted and thus used. In this chapter, we present a distributed architecture for managing IoT data extraction and processing that also includes algorithms for the assessment of data quality and security levels of considered sources. A prototype of such an architecture has been realized; through a user interface, it is possible to access data services able to filter data from IoT devices on the basis of security and data quality requirements. The chapter describes the prototype and shows some experiments performed by using several real-time open data feeds characterized by different levels of reliability, quality and security.
Studies in Computational Intelligence
978-3-319-58189-7
978-3-319-58190-3
Data quality; Internet of Things; Middleware; Security; Artificial Intelligence
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1048845
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