Recent advances on federated learning for cybersecurity and cybersecurity for federated learning for internet of things

B Ghimire, DB Rawat - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the
emerging Internet of Things (IoT) has gained a lot of attention from the government …

[HTML][HTML] Federated learning for secure IoMT-applications in smart healthcare systems: A comprehensive review

S Rani, A Kataria, S Kumar, P Tiwari - Knowledge-based systems, 2023 - Elsevier
Recent developments in the Internet of Things (IoT) and various communication
technologies have reshaped numerous application areas. Nowadays, IoT is assimilated into …

A survey of machine unlearning

TT Nguyen, TT Huynh, Z Ren, PL Nguyen… - ar**
X Cao, M Fang, J Liu, NZ Gong - arxiv preprint arxiv:2012.13995, 2020 - arxiv.org
Byzantine-robust federated learning aims to enable a service provider to learn an accurate
global model when a bounded number of clients are malicious. The key idea of existing …

Machine learning for healthcare wearable devices: the big picture

F Sabry, T Eltaras, W Labda, K Alzoubi… - Journal of Healthcare …, 2022 - Wiley Online Library
Using artificial intelligence and machine learning techniques in healthcare applications has
been actively researched over the last few years. It holds promising opportunities as it is …

Sensor-based and vision-based human activity recognition: A comprehensive survey

LM Dang, K Min, H Wang, MJ Piran, CH Lee, H Moon - Pattern Recognition, 2020 - Elsevier
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …