Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)

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Efficient IDS System Using Hybrid Machine Learning Mechanism in IoT

Authors
Tina Yadav1, *, Devender Kumar2
1Research Scholar, Department of Computer Science & Applications, Baba Mastnath University, Rohtak, Haryana, India
2Associate Professor, Department of Computer Science & Applications, Baba Mastnath University, Rohtak, Haryana, India
*Corresponding author. Email: tinayadav772@gmail.com
Corresponding Author
Tina Yadav
Available Online 25 June 2025.
DOI
10.2991/978-94-6463-740-3_20How to use a DOI?
Keywords
IDS; Machine Learning; Accuracy; Performance; IoT
Abstract

This paper investigates the important need for more robust IoT security policies. It looks at the prospect that using machine learning methods to improve the accuracy and efficiency of IDS might help them The spread of linked devices makes protecting IoT settings from cyberattacks a priority. Our approach is on real-time network traffic pattern analysis to distinguish between benign and hostile behaviour. One may achieve this by using machine learning techniques. The approach extracts valuable knowledge from a wide spectrum of IoT data sources by means of feature engineering. Another component of it is choosing machine learning models deliberately for adaptive learning. Apart from evaluating the influence of the improved intrusion detection system on network performance, this study addresses problems like data imbalance and resource constraints. The objective is to save time and resource use while nevertheless attaining a great degree of precision. Investigating other processing methods and increasing computer efficiency will help us to do this. Crucially, the results of this research have great relevance for enhancing IoT settings’ security. These findings have led to a scalable and adaptable solution to the issue of developing cyber threats being suggested.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)
Series
Advances in Intelligent Systems Research
Publication Date
25 June 2025
ISBN
978-94-6463-740-3
ISSN
1951-6851
DOI
10.2991/978-94-6463-740-3_20How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Tina Yadav
AU  - Devender Kumar
PY  - 2025
DA  - 2025/06/25
TI  - Efficient IDS System Using Hybrid Machine Learning Mechanism in IoT
BT  - Proceedings of the 6th International Conference on Deep Learning, Artificial Intelligence and Robotics (ICDLAIR 2024)
PB  - Atlantis Press
SP  - 225
EP  - 239
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-740-3_20
DO  - 10.2991/978-94-6463-740-3_20
ID  - Yadav2025
ER  -