Federated learning for 6G-enabled secure communication systems: a comprehensive survey
Abstract Machine learning (ML) and Deep learning (DL) models are popular in many areas,
from business, medicine, industries, healthcare, transportation, smart cities, and many more …
from business, medicine, industries, healthcare, transportation, smart cities, and many more …
Federated deep learning for cyber security in the internet of things: Concepts, applications, and experimental analysis
In this article, we present a comprehensive study with an experimental analysis of federated
deep learning approaches for cyber security in the Internet of Things (IoT) applications …
deep learning approaches for cyber security in the Internet of Things (IoT) applications …
The duo of artificial intelligence and big data for industry 4.0: Applications, techniques, challenges, and future research directions
SK Jagatheesaperumal, M Rahouti… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The increasing need for economic, safe, and sustainable smart manufacturing combined
with novel technological enablers has paved the way for artificial intelligence (AI) and big …
with novel technological enablers has paved the way for artificial intelligence (AI) and big …
A systematic review of data-driven attack detection trends in IoT
The Internet of Things is perhaps a concept that the world cannot be imagined without today,
having become intertwined in our everyday lives in the domestic, corporate and industrial …
having become intertwined in our everyday lives in the domestic, corporate and industrial …
Accuracy and diversity-aware multi-objective approach for random forest construction
NEI Karabadji, AA Korba, A Assi, H Seridi… - Expert Systems with …, 2023 - Elsevier
Random Forest is an ensemble classification approach. It aims to design a discrete finite
group of decision trees constructed based on bootstrap samples and random attribute …
group of decision trees constructed based on bootstrap samples and random attribute …
Semisupervised federated-learning-based intrusion detection method for internet of things
Federated learning (FL) has become an increasingly popular solution for intrusion detection
to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based …
to avoid data privacy leakage in Internet of Things (IoT) edge devices. Existing FL-based …
Fedgan-ids: Privacy-preserving ids using gan and federated learning
Federated Learning (FL) is a promising distributed training model that aims to minimize the
data sharing to enhance privacy and performance. FL requires sufficient and diverse training …
data sharing to enhance privacy and performance. FL requires sufficient and diverse training …
Federated semisupervised learning for attack detection in industrial Internet of Things
Security has become a critical issue for Industry4. 0 due to different emerging cyber-security
threats. Recently, many deep learning (DL) approaches have focused on intrusion detection …
threats. Recently, many deep learning (DL) approaches have focused on intrusion detection …
Federated intrusion detection in blockchain-based smart transportation systems
M Abdel-Basset, N Moustafa, H Hawash… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
With the integration of the Internet of Things (IoT) in the field of transportation, the Internet of
Vehicles (IoV) turned to be a vital method for designing Smart Transportation Systems (STS) …
Vehicles (IoV) turned to be a vital method for designing Smart Transportation Systems (STS) …
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 …