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2022 | OriginalPaper | Chapter

Application of Machine Learning Algorithms in Ensuring Information Security of the Internet of Things in Water Transport

Authors : Izolda Li, Artem Arbuzov, Vladimir Shilkin, Irina Shilkina, Nadezhda Baryshnikova

Published in: Safety in Aviation and Space Technologies

Publisher: Springer International Publishing

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Abstract

IoT technologies are gaining increasing influence in all areas of human activity from wearable devices to industrial applications. With the rapid development of water transport infrastructure, as well as with the growth of commissioned port and berthing mechanisms, serious prerequisites have arisen for the use of control and monitoring tools. IoT systems allow you to flexibly and efficiently solve such problems. The IoT architecture includes various levels of communication and information transfer. There are many protocols and applications running at each layer, which can be vulnerable to attacks of intruders. Nowadays, research related to solving IoT security issues using various technologies and concepts, such as blockchain, statistical analysis, machine learning, etc., is actively underway. This paper provides an overview of machine learning methods used at various layers of the Internet of Things architecture. In addition to the layers of the IoT architecture, it also discusses the machine learning methods used to counter the increasingly widespread attacks of social engineering that lead to the loss of integrity, confidentiality and availability of information. At the end of the paper, the machine learning methods that best match the architectural and hardware capabilities of the IoT were selected.

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Metadata
Title
Application of Machine Learning Algorithms in Ensuring Information Security of the Internet of Things in Water Transport
Authors
Izolda Li
Artem Arbuzov
Vladimir Shilkin
Irina Shilkina
Nadezhda Baryshnikova
Copyright Year
2022
DOI
https://doi.org/10.1007/978-3-030-85057-9_45

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