Internet of Things (IoT) security with blockchain technology: A state-of-the-art review

AA Khan, AA Laghari, ZA Shaikh… - IEEE …, 2022 - ieeexplore.ieee.org
With the rapid enhancement in the design and development of the Internet of Things creates
a new research interest in the adaptation in industrial domains. It is due to the impact of …

Federated learning for intrusion detection system: Concepts, challenges and future directions

S Agrawal, S Sarkar, O Aouedi, G Yenduri… - Computer …, 2022 - Elsevier
The rapid development of the Internet and smart devices trigger surge in network traffic
making its infrastructure more complex and heterogeneous. The predominated usage of …

Federated deep learning for zero-day botnet attack detection in IoT-edge devices

SI Popoola, R Ande, B Adebisi, G Gui… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Deep learning (DL) has been widely proposed for botnet attack detection in Internet of
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …

Federated deep learning for cyber security in the internet of things: Concepts, applications, and experimental analysis

MA Ferrag, O Friha, L Maglaras, H Janicke… - IEEE Access, 2021 - ieeexplore.ieee.org
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 …

A survey on deep learning for cybersecurity: Progress, challenges, and opportunities

M Macas, C Wu, W Fuertes - Computer Networks, 2022 - Elsevier
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …

Federated reinforcement learning: Techniques, applications, and open challenges

J Qi, Q Zhou, L Lei, K Zheng - arXiv preprint arXiv:2108.11887, 2021 - arxiv.org
This paper presents a comprehensive survey of Federated Reinforcement Learning (FRL),
an emerging and promising field in Reinforcement Learning (RL). Starting with a tutorial of …

Detecting cyberattacks using anomaly detection in industrial control systems: A federated learning approach

TT Huong, TP Bac, DM Long, TD Luong, NM Dan… - Computers in …, 2021 - Elsevier
In recent years, the rapid development and wide application of advanced technologies have
profoundly impacted industrial manufacturing, leading to smart manufacturing (SM) …

Distributed anomaly detection in smart grids: a federated learning-based approach

J Jithish, B Alangot, N Mahalingam, KS Yeo - IEEE Access, 2023 - ieeexplore.ieee.org
The smart grid integrates Information and Communication Technologies (ICT) into the
traditional power grid to manage the generation, distribution, and consumption of electrical …

On the feasibility of federated learning towards on-demand client deployment at the edge

M Chahoud, S Otoum, A Mourad - Information Processing & Management, 2023 - Elsevier
Nowadays, researchers are investing their time and devoting their efforts in developing and
motivating the 6G vision and resources that are not available in 5G. Edge computing and …

Efficient intrusion detection toward IoT networks using cloud–edge collaboration

R Yang, H He, Y Xu, B Xin, Y Wang, Y Qu, W Zhang - Computer Networks, 2023 - Elsevier
Abstract The Internet of Things (IoT) is increasingly utilized in daily life and industrial
production, particularly in critical infrastructures. IoT cybersecurity has an effect on people's …