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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.
Afiliação
  • Anwar RW; Faculty of Computer Studies (FCS), Arab Open University, Muscat P.O. Box 1596, Oman.
  • Qureshi KN; Department of Electronic & Computer Engineering, University of Limerick, V94 T9PX Limerick, Ireland.
  • Nagmeldin W; Department of Information Systems, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia.
  • Abdelmaboud A; Department of Information Systems, College of Science and Arts, King Khalid University, Muhayil Asir 61913, Saudi Arabia.
  • Ghafoor KZ; Department of Computer Science, Knowledge University, University Park, Kirkuk Road, Erbil 446015, Iraq.
  • Javed IT; Center of Excellence in Artificial Intelligence (CoE-AI), Department of Computer Science, Bahria University, Islamabad 44000, Pakistan.
  • Crespi N; Institut Polytechnique de Paris Telecom SudParis Evry, Courcouronnes FR, 9 Rue Charles Fourier, 91000 Evry, France.
Sensors (Basel) ; 22(19)2022 Sep 22.
Article em En | MEDLINE | ID: mdl-36236298
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ciência de Dados / Internet das Coisas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Ciência de Dados / Internet das Coisas Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article