Federated learning for smart healthcare: A survey

DC Nguyen, QV Pham, PN Pathirana, M Ding… - ACM Computing …, 2022 - dl.acm.org
Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT)
have transformed smart healthcare enabled by artificial intelligence (AI). Traditionally, AI …

Federated learning for privacy preservation in smart healthcare systems: A comprehensive survey

M Ali, F Naeem, M Tariq… - IEEE journal of biomedical …, 2022 - ieeexplore.ieee.org
Recent advances in electronic devices and communication infrastructure have
revolutionized the traditional healthcare system into a smart healthcare system by using …

Incentive mechanisms for federated learning: From economic and game theoretic perspective

X Tu, K Zhu, NC Luong, D Niyato… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Federated learning (FL) becomes popular and has shown great potentials in training large-
scale machine learning (ML) models without exposing the owners' raw data. In FL, the data …

Gtg-shapley: Efficient and accurate participant contribution evaluation in federated learning

Z Liu, Y Chen, H Yu, Y Liu, L Cui - ACM Transactions on intelligent …, 2022 - dl.acm.org
Federated Learning (FL) bridges the gap between collaborative machine learning and
preserving data privacy. To sustain the long-term operation of an FL ecosystem, it is …

A comprehensive survey of incentive mechanism for federated learning

R Zeng, C Zeng, X Wang, B Li, X Chu - arxiv preprint arxiv:2106.15406, 2021 - arxiv.org
Federated learning utilizes various resources provided by participants to collaboratively train
a global model, which potentially address the data privacy issue of machine learning. In …

Adoption of federated learning for healthcare informatics: Emerging applications and future directions

VA Patel, P Bhattacharya, S Tanwar, R Gupta… - IEEE …, 2022 - ieeexplore.ieee.org
The smart healthcare system has improved the patients quality of life (QoL), where the
records are being analyzed remotely by distributed stakeholders. It requires a voluminous …

A survey on decentralized federated learning

E Gabrielli, G Pica, G Tolomei - arxiv preprint arxiv:2308.04604, 2023 - arxiv.org
In recent years, federated learning (FL) has become a very popular paradigm for training
distributed, large-scale, and privacy-preserving machine learning (ML) systems. In contrast …

A robust game-theoretical federated learning framework with joint differential privacy

L Zhang, T Zhu, P **ong, W Zhou… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Federated learning is a promising distributed machine learning paradigm that has been
playing a significant role in providing privacy-preserving learning solutions. However …

Economic systems in the metaverse: Basics, state of the art, and challenges

H Huawei, Z Qinnan, L Taotao, Y Qinglin… - ACM Computing …, 2023 - dl.acm.org
Economic systems play pivotal roles in the metaverse. However, we have not yet found an
overview that systematically introduces economic systems for the metaverse. Therefore, we …

Survey on federated learning for intrusion detection system: Concept, architectures, aggregation strategies, challenges, and future directions

A Khraisat, A Alazab, S Singh, T Jan… - ACM Computing …, 2024 - dl.acm.org
Intrusion Detection Systems (IDS) are essential for securing computer networks by
identifying and mitigating potential threats. However, traditional IDS face challenges related …