[HTML][HTML] Deep learning for cyber threat detection in IoT networks: A review

A Aldhaheri, F Alwahedi, MA Ferrag, A Battah - Internet of Things and Cyber …, 2024 - Elsevier
Abstract The Internet of Things (IoT) has revolutionized modern tech with interconnected
smart devices. While these innovations offer unprecedented opportunities, they also …

Empowering non-terrestrial networks with artificial intelligence: A survey

A Iqbal, ML Tham, YJ Wong, G Wainer, YX Zhu… - IEEE …, 2023 - ieeexplore.ieee.org
6G networks can support global, ubiquitous and seamless connectivity through the
convergence of terrestrial and non-terrestrial networks (NTNs). Unlike terrestrial scenarios …

Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction

MA Talukder, MM Islam, MA Uddin, KF Hasan… - Journal of big …, 2024 - Springer
Cybersecurity has emerged as a critical global concern. Intrusion Detection Systems (IDS)
play a critical role in protecting interconnected networks by detecting malicious actors and …

Deep Reinforcement Learning for intrusion detection in Internet of Things: Best practices, lessons learnt, and open challenges

A Rizzardi, S Sicari, AC Porisini - Computer Networks, 2023 - Elsevier
Abstract The Internet of Things (IoT) scenario places important challenges even for deep
learning-based intrusion detection systems. IoTs are highly heterogeneous networks in …

Optimizing Network Security with Machine Learning and Multi-Factor Authentication for Enhanced Intrusion Detection

RK Mahmood, AI Mahameed, NQ Lateef… - Journal of Robotics …, 2024 - journal.umy.ac.id
This study examines the utilization of machine learning methodologies and multi-factor
authentication (MFA) to bolster network security, specifically targeting network intrusion …

Breaking alert fatigue: Ai-assisted siem framework for effective incident response

T Ban, T Takahashi, S Ndichu, D Inoue - Applied Sciences, 2023 - mdpi.com
Contemporary security information and event management (SIEM) solutions struggle to
identify critical security incidents effectively due to the overwhelming number of false alerts …

A Survey of Deep Learning Technologies for Intrusion Detection in Internet of Things

H Liao, MZ Murah, MK Hasan, AHM Aman… - IEEE …, 2024 - ieeexplore.ieee.org
The Internet of Things (IoT) is transforming how we live and work, and its applications are
widespread, spanning smart homes, industrial monitoring, smart cities, healthcare …

Next Generation AI-Based Firewalls: A Comparative Study

S Ahmadi - International Journal of Computer (IJC), 2023 - hal.science
Cybersecurity is a critical concern in the digital age, demanding innovative approaches to
safeguard sensitive information and systems. This paper conducts a thorough examination …

Sliding principal component and dynamic reward reinforcement learning based IIoT attack detection

V Ellappan, A Mahendran, M Subramanian… - Scientific Reports, 2023 - nature.com
Abstract The Internet of Things (IoT) involves the gathering of all those devices that connect
to the Internet with the purpose of collecting and sharing data. The application of IoT in the …