Edge learning for 6G-enabled Internet of Things: A comprehensive survey of vulnerabilities, datasets, and defenses

MA Ferrag, O Friha, B Kantarci… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The deployment of the fifth-generation (5G) wireless networks in Internet of Everything (IoE)
applications and future networks (eg, sixth-generation (6G) networks) has raised a number …

[HTML][HTML] Unleashing the potential of sixth generation (6G) wireless networks in smart energy grid management: A comprehensive review

MH Alsharif, A Jahid, R Kannadasan, MK Kim - Energy Reports, 2024 - Elsevier
As the world continues to seek sustainable and efficient energy solutions, the integration of
advanced technologies into smart energy grid management (SEGM) becomes a paramount …

A survey on explainable ai for 6g o-ran: Architecture, use cases, challenges and research directions

B Brik, H Chergui, L Zanzi, F Devoti, A Ksentini… - arXiv preprint arXiv …, 2023 - arxiv.org
The recent O-RAN specifications promote the evolution of RAN architecture by function
disaggregation, adoption of open interfaces, and instantiation of a hierarchical closed-loop …

Survey on Unified Threat Management (UTM) Systems for Home Networks

A Siddiqui, BP Rimal, M Reisslein… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Home networks increasingly support important networked applications with limited
professional network administration support, while sophisticated attacks pose enormous …

Secure video offloading in multi-UAV-enabled MEC networks: A deep reinforcement learning approach

T Zhao, F Li, L He - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV)-enabled mobile-edge computing (MEC) has been widely
applied in Internet of Things networks while the security risk of wireless computation …

Blockchain-Based Federated Learning with Enhanced Privacy and Security Using Homomorphic Encryption and Reputation

R Yang, T Zhao, FR Yu, M Li, D Zhang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Federated learning, leveraging distributed data from multiple nodes to train a common
model, allows for the use of more data to improve the model while also protecting the privacy …

Physical Layer Covert Communication in B5G Wireless Networks—Its Research, Applications, and Challenges

Y Jiang, L Wang, HH Chen, X Shen - Proceedings of the IEEE, 2024 - ieeexplore.ieee.org
Physical layer covert communication is a crucial secure communication technology that
enables a transmitter to convey information covertly to a recipient without being detected by …

Cybersecurity of Satellite Communications Systems: A Comprehensive Survey of the Space, Ground, and Links Segments

S Salim, N Moustafa, M Reisslein - … Communications Surveys & …, 2024 - ieeexplore.ieee.org
Satellite communications (Satcoms) systems have become an integral part of modern
society, providing critical infrastructure for a wide range of applications. However, as the …

Adversarial Attacks and Defenses in 6G Network-Assisted IoT Systems

BD Son, NT Hoa, T Van Chien, W Khalid… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
The Internet of Things (IoT) and massive IoT systems are key to sixth-generation (6G)
networks due to dense connectivity, ultrareliability, low latency, and high throughput …

Trust Management of Tiny Federated Learning in Internet of Unmanned Aerial Vehicles

J Zheng, J Xu, H Du, D Niyato, J Kang… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Lightweight training and distributed tiny data storage in the local model will lead to the
severe challenge of convergence for tiny federated learning (FL). Achieving fast …