An adaptable Intelligence Algorithm to a Cybersecurity Framework for IIOT
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The industrial internet of things (IIoT) has grown in recent years, which makes it possible to publicize new technological innovations and be able to integrate them with each other, such as smart cities among other applications such as: health, education, traffic among others , but at the same time there is a problem that is security, since lately there have been several security incidents related to IIoT, more specifically to the networks that handle these technologies such as: ISPs (Internet Service Provider), which makes it necessary to adopt and investigate the inclusion of artificial intelligence in cybersecurity, which this provides new paradigms that will help in a satisfactory solution (1)The Objective was propose an intelligence technique adaptable to a cybersecurity framework with the ability to solve network security problems in IIoT devices. For the development of this work, the action research methodology (IA) is used, which consists of uniting theory with practice in such a way that the researcher can draw correct conclusions about the practices carried out. Because this type of methodology seeks to solve specific problems in a specific community, continuously managing to understand and interpret to improve from them (2). It has been found that there are a great variety of intelligence techniques such as Deep Learning deep learning, which obtained a very high score in the characterization due to its great possibilities when integrating the algorithm into the field of cybersecurity. very little characterized; However, in the initial research that was carried out, the result was how to work with this technology and how to adapt it to cybersecurity. There are different ways to analyze and secure data on the network, one of those are learning techniques, in this research several techniques were identified that with their respective algorithms that provided the basis for adaptability with a framework related to IIoT technologies.
Santiago Ordoñez Tumbo, Institución Universitaria Colegio Mayor del Cauca, Faculty of Engineering, Computing Engineering Program, I+D in Computing Group, Popayán-Colombia
https://orcid.org/0000-0001-7420-5410
Katerine Márceles Villalba, Institución Universitaria Colegio Mayor del Cauca, Faculty of Engineering, Computing Engineering Program, I+D in Computing Group, Popayán-Colombia
https://orcid.org/0000-0002-4571-0714
Siler Amador Donado, Universidad del Cauca, Faculty of Electronic Engineering and Telecommunicatios, System Engineering Program, Information Technology Research and Development Group (GTI), Popayán-Colombia
https://orcid.org/0000-0002-4571-8273
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Accepted 2022-01-20
Published 2022-05-26
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