MAGRU-IDS: A multi-head attention-based gated recurrent unit for intrusion detection in IIoT networks
The increasing prevalence of the Industrial Internet of Things (IIoT) in industrial
environments amplifies the potential for security breaches and compromises. To monitor IIoT …
environments amplifies the potential for security breaches and compromises. To monitor IIoT …
ABDNN-IDS: Attention-Based Deep Neural Networks for Intrusion Detection in Industrial IoT
The increasing trend of the Industrial Internet of Things (IIoT) within industrial environments
magnifies the risk of security breaches and vulnerabilities. Maintaining confidentiality is a …
magnifies the risk of security breaches and vulnerabilities. Maintaining confidentiality is a …
ADCL: toward an adaptive network intrusion detection system using collaborative learning in IoT networks
With the widespread of cyber attacks, network intrusion detection system (NIDS) is becoming
an important and essential tool to protect Internet of Things (IoT) environments. However, it …
an important and essential tool to protect Internet of Things (IoT) environments. However, it …
A Self-Attention-Based Deep Convolutional Neural Networks for IIoT Networks Intrusion Detection
The Industrial Internet of Things (IIoT) comprises a variety of systems, smart devices, and an
extensive range of communication protocols. Hence, these systems face susceptibility to …
extensive range of communication protocols. Hence, these systems face susceptibility to …
Feature analysis for machine learning-based IoT intrusion detection
Internet of Things (IoT) networks have become an increasingly attractive target of
cyberattacks. Powerful Machine Learning (ML) models have recently been adopted to …
cyberattacks. Powerful Machine Learning (ML) models have recently been adopted to …
All predict wisest decides: A novel ensemble method to detect intrusive traffic in iot networks
Internet of things (IoT) networks confront vari-ous network intrusion threats due to massively
interconnected nodes that form an extensive attack surface for adversaries. Machine …
interconnected nodes that form an extensive attack surface for adversaries. Machine …
An end-to-end learning approach for enhancing intrusion detection in Industrial-Internet of Things
K Hassini, S Khalis, O Habibi, M Chemmakha… - Knowledge-Based …, 2024 - Elsevier
Abstract The Industrial-Internet of Things (I-IoT) stands out as one of the most dynamically
evolving subfields within the expansive realm of the Internet of Things (IoT). Its exponential …
evolving subfields within the expansive realm of the Internet of Things (IoT). Its exponential …
ERID: A deep learning-based approach towards efficient real-time intrusion detection for IoT
M Lin, B Zhao, Q Xin - 2020 IEEE eighth international …, 2020 - ieeexplore.ieee.org
In the 5G and Internet of Things (IoT) era, the threat of network intrusions has greatly affected
people's work and life. The increasing complexity of intelligent devices in IoT brings huge …
people's work and life. The increasing complexity of intelligent devices in IoT brings huge …
A machine learning framework for intrusion detection system in iot networks using an ensemble feature selection method
G Guo - 2021 IEEE 12th Annual Information Technology …, 2021 - ieeexplore.ieee.org
During the recent years, there has been an escalated growth of the Internet of Things (IoT)
devices in our daily lives. Due to their inherent vulnerabilities, IoT networks are more …
devices in our daily lives. Due to their inherent vulnerabilities, IoT networks are more …
An explainable ensemble deep learning approach for intrusion detection in industrial Internet of Things
Ensuring the security of critical Industrial Internet of Things (IIoT) systems is of utmost
importance, with a primary focus on identifying cyber-attacks using Intrusion Detection …
importance, with a primary focus on identifying cyber-attacks using Intrusion Detection …