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Data Analytics, Self-Organization, and Security Provisioning for Smart Monitoring Systems
Internet availability and its integration with smart technologies have favored everyday objects and things and offered new areas, such as the Internet of Things (IoT). IoT refers to a concept where smart devices or things are connected and create a network. This new area has suffered from big data h...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571973/ https://www.ncbi.nlm.nih.gov/pubmed/36236298 http://dx.doi.org/10.3390/s22197201 |
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author | Anwar, Raja Waseem Qureshi, Kashif Naseer Nagmeldin, Wamda Abdelmaboud, Abdelzahir Ghafoor, Kayhan Zrar Javed, Ibrahim Tariq Crespi, Noel |
author_facet | Anwar, Raja Waseem Qureshi, Kashif Naseer Nagmeldin, Wamda Abdelmaboud, Abdelzahir Ghafoor, Kayhan Zrar Javed, Ibrahim Tariq Crespi, Noel |
author_sort | Anwar, Raja Waseem |
collection | PubMed |
description | Internet availability and its integration with smart technologies have favored everyday objects and things and offered new areas, such as the Internet of Things (IoT). IoT refers to a concept where smart devices or things are connected and create a network. This new area has suffered from big data handling and security issues. There is a need to design a data analytics model by using new 5G technologies, architecture, and a security model. Reliable data communication in the presence of legitimate nodes is always one of the challenges in these networks. Malicious nodes are generating inaccurate information and breach the user’s security. In this paper, a data analytics model and self-organizing architecture for IoT networks are proposed to understand the different layers of technologies and processes. The proposed model is designed for smart environmental monitoring systems. This paper also proposes a security model based on an authentication, detection, and prediction mechanism for IoT networks. The proposed model enhances security and protects the network from DoS and DDoS attacks. The proposed model evaluates in terms of accuracy, sensitivity, and specificity by using machine learning algorithms. |
format | Online Article Text |
id | pubmed-9571973 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-95719732022-10-17 Data Analytics, Self-Organization, and Security Provisioning for Smart Monitoring Systems Anwar, Raja Waseem Qureshi, Kashif Naseer Nagmeldin, Wamda Abdelmaboud, Abdelzahir Ghafoor, Kayhan Zrar Javed, Ibrahim Tariq Crespi, Noel Sensors (Basel) Article Internet availability and its integration with smart technologies have favored everyday objects and things and offered new areas, such as the Internet of Things (IoT). IoT refers to a concept where smart devices or things are connected and create a network. This new area has suffered from big data handling and security issues. There is a need to design a data analytics model by using new 5G technologies, architecture, and a security model. Reliable data communication in the presence of legitimate nodes is always one of the challenges in these networks. Malicious nodes are generating inaccurate information and breach the user’s security. In this paper, a data analytics model and self-organizing architecture for IoT networks are proposed to understand the different layers of technologies and processes. The proposed model is designed for smart environmental monitoring systems. This paper also proposes a security model based on an authentication, detection, and prediction mechanism for IoT networks. The proposed model enhances security and protects the network from DoS and DDoS attacks. The proposed model evaluates in terms of accuracy, sensitivity, and specificity by using machine learning algorithms. MDPI 2022-09-22 /pmc/articles/PMC9571973/ /pubmed/36236298 http://dx.doi.org/10.3390/s22197201 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Anwar, Raja Waseem Qureshi, Kashif Naseer Nagmeldin, Wamda Abdelmaboud, Abdelzahir Ghafoor, Kayhan Zrar Javed, Ibrahim Tariq Crespi, Noel Data Analytics, Self-Organization, and Security Provisioning for Smart Monitoring Systems |
title | Data Analytics, Self-Organization, and Security Provisioning for Smart Monitoring Systems |
title_full | Data Analytics, Self-Organization, and Security Provisioning for Smart Monitoring Systems |
title_fullStr | Data Analytics, Self-Organization, and Security Provisioning for Smart Monitoring Systems |
title_full_unstemmed | Data Analytics, Self-Organization, and Security Provisioning for Smart Monitoring Systems |
title_short | Data Analytics, Self-Organization, and Security Provisioning for Smart Monitoring Systems |
title_sort | data analytics, self-organization, and security provisioning for smart monitoring systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9571973/ https://www.ncbi.nlm.nih.gov/pubmed/36236298 http://dx.doi.org/10.3390/s22197201 |
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