A survey on intelligent Internet of Things: Applications, security, privacy, and future directions

O Aouedi, TH Vu, A Sacco, DC Nguyen… - … surveys & tutorials, 2024 - ieeexplore.ieee.org
The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …

Recent endeavors in machine learning-powered intrusion detection systems for the internet of things

D Manivannan - Journal of Network and Computer Applications, 2024 - Elsevier
The significant advancements in sensors and other resource-constrained devices, capable
of collecting data and communicating wirelessly, are poised to revolutionize numerous …

Revolutionizing cyber threat detection with large language models: A privacy-preserving bert-based lightweight model for iot/iiot devices

MA Ferrag, M Ndhlovu, N Tihanyi, LC Cordeiro… - IEEe …, 2024 - ieeexplore.ieee.org
The field of Natural Language Processing (NLP) is currently undergoing a revolutionary
transformation driven by the power of pre-trained Large Language Models (LLMs) based on …

[HTML][HTML] Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions

JPA Yaacoub, HN Noura, O Salman - Internet of Things and Cyber-Physical …, 2023 - Elsevier
Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …

[PDF][PDF] Revolutionizing cyber threat detection with large language models

MA Ferrag, M Ndhlovu, N Tihanyi… - arxiv preprint arxiv …, 2023 - academia.edu
Natural Language Processing (NLP) domain is experiencing a revolution due to the
capabilities of Pre-trained Large Language Models (LLMs), fueled by ground-breaking …

Digital twin and federated learning enabled cyberthreat detection system for IoT networks

MM Salim, D Camacho, JH Park - Future Generation Computer Systems, 2024 - Elsevier
The widespread deployment of Internet of Things (IoT) devices across various smart city
applications presents significant security challenges, increased by the rapidly evolving …

Federated deep learning for intrusion detection in consumer-centric internet of things

SI Popoola, AL Imoize, M Hammoudeh… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Consumer-centric Internet of Things (CIoT) will play a pivotal role in the fifth industrial
revolution (Industry 5.0) but it exhibits vulnerabilities that can render it susceptible to various …

[HTML][HTML] Deep neural decision forest (DNDF): A novel approach for enhancing intrusion detection systems in network traffic analysis

FS Alrayes, M Zakariah, M Driss, W Boulila - Sensors, 2023 - mdpi.com
Intrusion detection systems, also known as IDSs, are widely regarded as one of the most
essential components of an organization's network security. This is because IDSs serve as …

Network intrusion detection and mitigation in SDN using deep learning models

M Maddu, YN Rao - International Journal of Information Security, 2024 - Springer
Abstract Software-Defined Networking (SDN) is a contemporary network strategy utilized
instead of a traditional network structure. It provides significantly more administrative …

Deep learning approaches for network traffic classification in the internet of things (iot): A survey

JH Kalwar, S Bhatti - arxiv preprint arxiv:2402.00920, 2024 - arxiv.org
The Internet of Things (IoT) has witnessed unprecedented growth, resulting in a massive
influx of diverse network traffic from interconnected devices. Effectively classifying this …