A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks

Year : 2025 | Volume : 12 | Issue : 01 | Page : 1 11
    By

    Ali H. Wheeb,

  • Munsifa Firdaus Khan,

  1. Associate Professor, Department of Computer Engineering, College of Engineering, University of Baghdad, Baghdad, Iraq
  2. Assistant Professor, Department of Computer Science and Engineering, Assam Downtown University, Guwahati, Assam, India

Abstract

The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, transportation, and everyday living environments. Nevertheless, IoT does have a drawback, though, and that is the absence of strong and reliable security mechanisms. The usage of IoT has a number of potential dangers. These involve the possibility of illegal data accessibility, and other cyberattacks such as ransomware, botnets, denial of service (DoS), and espionage. The main focus outlined below is the application of machine learning (ML) algorithms for detecting network intrusions. When developing intrusion detection systems to identify network abnormalities, ML is a key component. ML algorithms are quite effective in identifying various forms of cyberattacks. The overview of several ML algorithms for detecting intrusions into IoT systems is presented in this research work. Algorithms such as support vector machines, random forests, and neural networks are essential for identifying anomalies in networks. To create intrusion detection systems, many datasets are available, such as CICIDS-2017, KDD-99, UNSW-NB 15, and TON_IoT. These datasets provide information on various kinds of cyberattacks. Further, challenges and security solutions for IoT Networks are discussed.

Keywords: Internet of things (IoT), machine learning (ML) algorithms, security solution, IDS, attack detection

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article:
Ali H. Wheeb, Munsifa Firdaus Khan. A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks. Journal of Artificial Intelligence Research & Advances. 2024; 12(01):1-11.
How to cite this URL:
Ali H. Wheeb, Munsifa Firdaus Khan. A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks. Journal of Artificial Intelligence Research & Advances. 2024; 12(01):1-11. Available from: https://journals.stmjournals.com/joaira/article=2024/view=191585


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Regular Issue Subscription Review Article
Volume 12
Issue 01
Received 14/12/2024
Accepted 20/12/2024
Published 30/12/2024
339

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