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 …
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 …
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 …
Abstract Nowadays, Multi Robotic System (MRS) consisting of different robot shapes, sizes and capabilities has received significant attention from researchers and are being deployed …
C Huang, G Xu, S Chen, W Zhou, EYK Ng… - Information …, 2022 - Elsevier
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 …
J Li, X Tong, J Liu, L Cheng - IEEE Systems Journal, 2023 - ieeexplore.ieee.org
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 …
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 …
Y Sun, H Ochiai, H Esaki - IEEE Transactions on Artificial …, 2021 - ieeexplore.ieee.org
Wider coverage and a better solution to a latency reduction in 5G necessitate its combination with multi-access edge computing technology. Decentralized deep learning …
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 …