[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 …

When federated learning meets privacy-preserving computation

J Chen, H Yan, Z Liu, M Zhang, H Xiong… - ACM Computing Surveys, 2024 - dl.acm.org
Nowadays, with the development of artificial intelligence (AI), privacy issues attract wide
attention from society and individuals. It is desirable to make the data available but invisible …

[HTML][HTML] Secure, privacy-preserving and federated machine learning in medical imaging

GA Kaissis, MR Makowski, D Rückert… - Nature Machine …, 2020 - nature.com
The broad application of artificial intelligence techniques in medicine is currently hindered
by limited dataset availability for algorithm training and validation, due to the absence of …

Edge and fog computing for IoT: A survey on current research activities & future directions

M Laroui, B Nour, H Moungla, MA Cherif, H Afifi… - Computer …, 2021 - Elsevier
Abstract The Internet of Things (IoT) allows communication between devices, things, and
any digital assets that send and receive data over a network without requiring interaction …

Blockchain-enabled federated learning data protection aggregation scheme with differential privacy and homomorphic encryption in IIoT

B Jia, X Zhang, J Liu, Y Zhang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
With rapid growth in data volume generated from different industrial devices in IoT, the
protection for sensitive and private data in data sharing has become crucial. At present …

A comprehensive survey on security, privacy issues and emerging defence technologies for UAVs

HJ Hadi, Y Cao, KU Nisa, AM Jamil, Q Ni - Journal of Network and …, 2023 - Elsevier
In the past two decades, there has been a rapid development in the drone industry known as
Unmanned Aerial Vehicles (UAVs). Currently, the use of commercial UAVs has increased a …

Trustworthy ai: A computational perspective

H Liu, Y Wang, W Fan, X Liu, Y Li, S Jain, Y Liu… - ACM Transactions on …, 2022 - dl.acm.org
In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …

Federated machine learning: Concept and applications

Q Yang, Y Liu, T Chen, Y Tong - ACM Transactions on Intelligent …, 2019 - dl.acm.org
Today's artificial intelligence still faces two major challenges. One is that, in most industries,
data exists in the form of isolated islands. The other is the strengthening of data privacy and …

[HTML][HTML] Privacy preservation in federated learning: An insightful survey from the GDPR perspective

N Truong, K Sun, S Wang, F Guitton, YK Guo - Computers & Security, 2021 - Elsevier
In recent years, along with the blooming of Machine Learning (ML)-based applications and
services, ensuring data privacy and security have become a critical obligation. ML-based …

On protecting the data privacy of large language models (llms): A survey

B Yan, K Li, M Xu, Y Dong, Y Zhang, Z Ren… - arXiv preprint arXiv …, 2024 - arxiv.org
Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …