An in-depth survey on virtualization technologies in 6g integrated terrestrial and non-terrestrial networks
6G networks are envisioned to deliver a large diversity of applications and meet stringent
Quality of Service (QoS) requirements. Hence, integrated Terrestrial and Non-Terrestrial …
Quality of Service (QoS) requirements. Hence, integrated Terrestrial and Non-Terrestrial …
Automated federated learning for intrusion detection of industrial control systems based on evolutionary neural architecture search
In recent years, federated learning has been applied to the security of the Internet of Things
and Industrial Control Systems (ICS) due to its advantages in communication cost and …
and Industrial Control Systems (ICS) due to its advantages in communication cost and …
[HTML][HTML] A federated learning-based zero trust intrusion detection system for Internet of Things
The rapid expansion of Internet of Things (IoT) devices presents unique challenges in
ensuring the security and privacy of interconnected systems. As cyberattacks become more …
ensuring the security and privacy of interconnected systems. As cyberattacks become more …
Against Network Attacks in Renewable Power Plants: Malicious Behavior Defense for Federated Learning
X Wu, Z Jin, J Zhou, K Liu, Z Liu - Computer Networks, 2024 - Elsevier
As reducing carbon emissions can relieve environmental concerns, networks-supported
renewable power plants are being built more and more. Inevitable network attacks have …
renewable power plants are being built more and more. Inevitable network attacks have …
Active ML for 6G: Towards Efficient Data Generation, Acquisition, and Annotation
This paper explores the integration of active machine learning (ML) for 6G networks, an area
that remains under-explored yet holds potential. Unlike passive ML systems, active ML can …
that remains under-explored yet holds potential. Unlike passive ML systems, active ML can …
Dynamic Federated Learning Aggregation for Enhanced Intrusion Detection in IoT Attacks
The widespread integration of Internet of Things (IoT) devices has elevated security risks,
specifically through vulnerabilities exploited by Botnet attacks. The emergence of these …
specifically through vulnerabilities exploited by Botnet attacks. The emergence of these …
A Survey on the Applications of Semi-Supervised Learning to Cyber-Security
Machine Learning's widespread application owes to its ability to develop accurate and
scalable models. In cyber-security, where labeled data is scarce, Semi-Supervised Learning …
scalable models. In cyber-security, where labeled data is scarce, Semi-Supervised Learning …
A novel approach to intrusion detection using zero-shot learning hybrid partial labels
Computer networks have become the backbone of our interconnected world in today's
technologically driven landscape. Unauthorized access or malicious activity carried out by …
technologically driven landscape. Unauthorized access or malicious activity carried out by …
Reinforcement Learning Approach for Traffic Congestion Prediction Empowered with Explainable Artificial Intelligence (XAI)
Traffic congestion in urban areas is an insistent challenge, increasing pollution levels and
economic inefficiencies while reducing quality of life. Traditional traffic management …
economic inefficiencies while reducing quality of life. Traditional traffic management …
Unleashing Security: Shaping the Resilient Future of 5G/B5G Network Orchestration
A Landa Arrue, A Urbieta, I Garitano - … (JNIC)(9ª. 2024. Sevilla)(2024), pp …, 2024 - idus.us.es
In the era of Industry 4.0, expanding device connectivity via 5G and Beyond 5G (B5G)
networks introduces significant security challenges, and advanced solutions for attack …
networks introduces significant security challenges, and advanced solutions for attack …