Robust machine learning based Intrusion detection system using simple statistical techniques in feature selection
Abstract There are serious security issues with the quick growth of IoT devices, which are increasingly essential to Industry 4.0. These gadgets frequently function in challenging environments with little energy and processing power, leaving them open to cyberattacks and making it more difficult to...
Saved in:
Main Authors: | Sunil Kaushik, Akashdeep Bhardwaj, Ahmad Almogren, Salil bharany, Ayman Altameem, Ateeq Ur Rehman, Seada Hussen, Habib Hamam |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-02-01
|
Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-025-88286-9 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Securing cyber-physical robotic systems for enhanced data security and real-time threat mitigation
by: Akashdeep Bhardwaj, et al.
Published: (2025-01-01) -
Efficient diagnosis of diabetes mellitus using an improved ensemble method
by: Blessing Oluwatobi Olorunfemi, et al.
Published: (2025-01-01) -
Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks
by: Nadia Shamshad, et al.
Published: (2025-01-01) -
Ensemble-based customer churn prediction in banking: a voting classifier approach for improved client retention using demographic and behavioral data
by: Ruchika Bhuria, et al.
Published: (2025-01-01) -
XI2S-IDS: An Explainable Intelligent 2-Stage Intrusion Detection System
by: Maiada M. Mahmoud, et al.
Published: (2025-01-01)