Machine and deep learning solutions for intrusion detection and prevention in IoTs: A survey

PLS Jayalaxmi, R Saha, G Kumar, M Conti… - IEEe Access, 2022 - ieeexplore.ieee.org
The increasing number of connected devices in the era of Internet of Thing (IoT) has also
increased the number intrusions. Intrusion Detection System (IDS) is a secondary intelligent …

[HTML][HTML] Internet of robotic things for mobile robots: concepts, technologies, challenges, applications, and future directions

H Kabir, ML Tham, YC Chang - Digital Communications and Networks, 2023 - Elsevier
Abstract Nowadays, Multi Robotic System (MRS) consisting of different robot shapes, sizes
and capabilities has received significant attention from researchers and are being deployed …

On the ICN-IoT with federated learning integration of communication: Concepts, security-privacy issues, applications, and future perspectives

A Rahman, K Hasan, D Kundu, MJ Islam… - Future Generation …, 2023 - Elsevier
The individual and integration use of the Internet of Things (IoT), Information-Centric
Networking (ICN), and Federated Learning (FL) have recently been used in several network …

A federated learning-based approach for improving intrusion detection in industrial internet of things networks

MM Rashid, SU Khan, F Eusufzai, MA Redwan… - Network, 2023 - mdpi.com
The Internet of Things (IoT) is a network of electrical devices that are connected to the
Internet wirelessly. This group of devices generates a large amount of data with information …

[HTML][HTML] Clustered federated learning architecture for network anomaly detection in large scale heterogeneous IoT networks

X Sáez-de-Cámara, JL Flores, C Arellano, A Urbieta… - Computers & …, 2023 - Elsevier
There is a growing trend of cyberattacks against Internet of Things (IoT) devices; moreover,
the sophistication and motivation of those attacks is increasing. The vast scale of IoT, diverse …

Fedgan-ids: Privacy-preserving ids using gan and federated learning

A Tabassum, A Erbad, W Lebda, A Mohamed… - Computer …, 2022 - Elsevier
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 …

Intrusion detection based on privacy-preserving federated learning for the industrial IoT

P Ruzafa-Alcázar, P Fernández-Saura… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Federated learning (FL) has attracted significant interest given its prominent advantages and
applicability in many scenarios. However, it has been demonstrated that sharing updated …

Federated semisupervised learning for attack detection in industrial internet of things

O Aouedi, K Piamrat, G Muller… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

Generalizing intrusion detection for heterogeneous networks: A stacked-unsupervised federated learning approach

G de Carvalho Bertoli, LAP Junior, O Saotome… - Computers & …, 2023 - Elsevier
The constantly evolving digital transformation imposes new requirements on our society.
Aspects relating to reliance on the networking domain and the difficulty of achieving security …

Security of Internet of Things (IoT) using federated learning and deep learning—Recent advancements, issues and prospects

V Gugueoth, S Safavat, S Shetty - ICT Express, 2023 - Elsevier
There is a great demand for an efficient security framework which can secure IoT systems
from potential adversarial attacks. However, it is challenging to design a suitable security …