Intelligent approaches toward intrusion detection systems for Industrial Internet of Things: A systematic comprehensive review
M Nuaimi, LC Fourati, BB Hamed - Journal of Network and Computer …, 2023 - Elsevier
Recently years, we have seen the exponential upgrowth of the Industrial Internet of Things
(IIoT), which brings significant benefits to our daily lives, industry, and society. The common …
(IIoT), which brings significant benefits to our daily lives, industry, and society. The common …
Intrusion detection system for large-scale IoT NetFlow networks using machine learning with modified Arithmetic Optimization Algorithm
With the rapid expansion of Internet of Things (IoT) networks, the need for robust security
measures to detect and report potential threats is becoming more urgent. In this paper, we …
measures to detect and report potential threats is becoming more urgent. In this paper, we …
A tree classifier based network intrusion detection model for Internet of Medical Things
Healthcare is one of the key areas of prospect for the Internet of Things (IoT). To facilitate
better medical services, enormous growth in the field of the Internet of Medical Things (IoMT) …
better medical services, enormous growth in the field of the Internet of Medical Things (IoMT) …
[HTML][HTML] Classification and explanation for intrusion detection system based on ensemble trees and SHAP method
In recent years, many methods for intrusion detection systems (IDS) have been designed
and developed in the research community, which have achieved a perfect detection rate …
and developed in the research community, which have achieved a perfect detection rate …
Anomal-E: A self-supervised network intrusion detection system based on graph neural networks
This paper investigates graph neural networks (GNNs) applied for self-supervised intrusion
and anomaly detection in computer networks. GNNs are a deep learning approach for graph …
and anomaly detection in computer networks. GNNs are a deep learning approach for graph …
An ensemble learning based intrusion detection model for industrial IoT security
M Mohy-Eddine, A Guezzaz… - Big Data Mining and …, 2023 - ieeexplore.ieee.org
Industrial Internet of Things (IIoT) represents the expansion of the Internet of Things (IoT) in
industrial sectors. It is designed to implicate embedded technologies in manufacturing fields …
industrial sectors. It is designed to implicate embedded technologies in manufacturing fields …
HBFL: A hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection
The continuous strengthening of the security posture of Internet of Things (IoT) ecosystems
is vital due to the increasing number of interconnected devices and the volume of sensitive …
is vital due to the increasing number of interconnected devices and the volume of sensitive …
Detection of real-time malicious intrusions and attacks in IoT empowered cybersecurity infrastructures
Computer viruses, malicious, and other hostile attacks can affect a computer network.
Intrusion detection is a key component of network security as an active defence technology …
Intrusion detection is a key component of network security as an active defence technology …
[HTML][HTML] Ensuring network security with a robust intrusion detection system using ensemble-based machine learning
MA Hossain, MS Islam - Array, 2023 - Elsevier
Intrusion detection is a critical aspect of network security to protect computer systems from
unauthorized access and attacks. The capacity of traditional intrusion detection systems …
unauthorized access and attacks. The capacity of traditional intrusion detection systems …
[HTML][HTML] Cyber threat intelligence sharing scheme based on federated learning for network intrusion detection
The uses of machine learning (ML) technologies in the detection of network attacks have
been proven to be effective when designed and evaluated using data samples originating …
been proven to be effective when designed and evaluated using data samples originating …