Um modelo ontológico e um serviço de gerenciamento de dados de apoio à privacidade na Internet das Coisas
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2019-02-08
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Universidade Federal de Goiás
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In the Internet of Things (IoT) paradigm, real-world objects equipped with identification, detection,
network, and processing capabilities communicate and consume services over the Internet to perform some
task on behalf of users. Due to the growing popularization of devices with sensing capabilities and the
consequent increase in data production from these devices, the literature states that the design of an
ontology-based model is an essential starting point for addressing privacy risks in IoT, since the connected
devices are increasingly able to monitor human activities. In addition, due to the complexity and dynamicity
of IoT environments, we emphasize the need for privacy ontologies that combine expressive and extensible
vocabulary but do not overload the processing of privacy data. Facing this problem, this work presents the
development of an ontology-based solution for privacy in IoT, composed by: i) IoT-Priv, a privacy
ontology for IoT, built as a light layer on IoT concepts imported from an emerging ontology, called IoTLite;
and ii) IoT-PrivServ, a privacy management service, which provides functionalities for consumers and
/ or producers who use the IoT-Priv ontology in modeling their data, abstracting from them the complexity
of perform such tasks. As contributions, the results of the evaluation of IoT-Priv and IoT-PrivServ indicate
that we maintained the lightness characteristic present in IoT-Lite, which was one of our initial goals. In
addition, we have demonstrated that IoT-Priv is expressive and extensible, since its concepts allow complex
scenarios to be modeled, and if necessary, the extension points included in the ontology allow it to be
imported and extended to meet more specific needs.
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ARRUDA, M. F. Um modelo ontológico e um serviço de gerenciamento de dados de apoio à privacidade na Internet das Coisas. 2019. 147 f. Dissertação (Mestrado em Ciência da Computação) - Universidade Federal de Goiás, Goiânia, 2019.