Security and privacy on 6g network edge: A survey
To meet the stringent service requirements of 6G applications such as immersive cloud
eXtended Reality (XR), holographic communication, and digital twin, there is no doubt that …
eXtended Reality (XR), holographic communication, and digital twin, there is no doubt that …
Federated learning for intrusion detection system: Concepts, challenges and future directions
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 …
making its infrastructure more complex and heterogeneous. The predominated usage of …
Federated deep learning for zero-day botnet attack detection in IoT-edge devices
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 …
Things (IoT) networks. However, the traditional centralized DL (CDL) method cannot be …
Blockchain and federated learning-based intrusion detection approaches for edge-enabled industrial IoT networks: A survey
S Ali, Q Li, A Yousafzai - Ad Hoc Networks, 2024 - Elsevier
The industrial internet of things (IIoT) is an evolutionary extension of the traditional Internet of
Things (IoT) into processes and machines for applications in the industrial sector. The IIoT …
Things (IoT) into processes and machines for applications in the industrial sector. The IIoT …
Generalizing intrusion detection for heterogeneous networks: A stacked-unsupervised federated learning approach
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 …
Aspects relating to reliance on the networking domain and the difficulty of achieving security …
[HTML][HTML] Internet of robotic things for mobile robots: concepts, technologies, challenges, applications, and future directions
Abstract Nowadays, Multi Robotic System (MRS) consisting of different robot shapes, sizes
and capabilities has received significant attention from researchers and are being deployed …
and capabilities has received significant attention from researchers and are being deployed …
The evolution of federated learning-based intrusion detection and mitigation: a survey
In 2016, Google introduced the concept of Federated Learning (FL), enabling collaborative
Machine Learning (ML). FL does not share local data but ML models, offering applications in …
Machine Learning (ML). FL does not share local data but ML models, offering applications in …
Federated learning for network attack detection using attention-based graph neural networks
W Jianping, Q Guangqiu, W Chunming, J Weiwei… - Scientific Reports, 2024 - nature.com
Federated Learning is an effective solution to address the issues of data isolation and
privacy leakage in machine learning. However, ensuring the security of network devices and …
privacy leakage in machine learning. However, ensuring the security of network devices and …
An efficient federated learning system for network intrusion detection
Network intrusion detection is used to detect unauthorized activities on a digital network,
with which the cybersecurity teams of organizations can then kick-start prevention protocols …
with which the cybersecurity teams of organizations can then kick-start prevention protocols …
An improved federated learning approach enhanced internet of health things framework for private decentralized distributed data
With the privacy protection increasingly being concerned, Data centralization often heavily
causes a big risk of privacy protection, gradually, there is a prevailing trend to enhance the …
causes a big risk of privacy protection, gradually, there is a prevailing trend to enhance the …