A comprehensive survey of privacy-preserving federated learning: A taxonomy, review, and future directions
The past four years have witnessed the rapid development of federated learning (FL).
However, new privacy concerns have also emerged during the aggregation of the …
However, new privacy concerns have also emerged during the aggregation of the …
A survey on federated learning: challenges and applications
J Wen, Z Zhang, Y Lan, Z Cui, J Cai… - International Journal of …, 2023 - Springer
Federated learning (FL) is a secure distributed machine learning paradigm that addresses
the issue of data silos in building a joint model. Its unique distributed training mode and the …
the issue of data silos in building a joint model. Its unique distributed training mode and the …
Privacy‐preserving federated learning based on multi‐key homomorphic encryption
With the advance of machine learning and the Internet of Things (IoT), security and privacy
have become critical concerns in mobile services and networks. Transferring data to a …
have become critical concerns in mobile services and networks. Transferring data to a …
Distillation-based semi-supervised federated learning for communication-efficient collaborative training with non-iid private data
This study develops a federated learning (FL) framework overcoming largely incremental
communication costs due to model sizes in typical frameworks without compromising model …
communication costs due to model sizes in typical frameworks without compromising model …
VFL: A verifiable federated learning with privacy-preserving for big data in industrial IoT
Due to the strong analytical ability of big data, deep learning has been widely applied to
model on the collected data in industrial Internet of Things (IoT). However, for privacy issues …
model on the collected data in industrial Internet of Things (IoT). However, for privacy issues …
On the ICN-IoT with federated learning integration of communication: Concepts, security-privacy issues, applications, and future perspectives
The individual and integration use of the Internet of Things (IoT), Information-Centric
Networking (ICN), and Federated Learning (FL) have recently been used in several network …
Networking (ICN), and Federated Learning (FL) have recently been used in several network …
Privacy-preserving aggregation in federated learning: A survey
Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …
and growing concerns over personal data privacy, Privacy-Preserving Federated Learning …
PVD-FL: A privacy-preserving and verifiable decentralized federated learning framework
Over the past years, the increasingly severe data island problem has spawned an emerging
distributed deep learning framework—federated learning, in which the global model can be …
distributed deep learning framework—federated learning, in which the global model can be …
Sok: Secure aggregation based on cryptographic schemes for federated learning
M Mansouri, M Önen, WB Jaballah… - Proceedings on Privacy …, 2023 - petsymposium.org
Secure aggregation consists of computing the sum of data collected from multiple sources
without disclosing these individual inputs. Secure aggregation has been found useful for …
without disclosing these individual inputs. Secure aggregation has been found useful for …
Efficiency optimization techniques in privacy-preserving federated learning with homomorphic encryption: A brief survey
Federated learning (FL) offers distributed machine learning on edge devices. However, the
FL model raises privacy concerns. Various techniques, such as homomorphic encryption …
FL model raises privacy concerns. Various techniques, such as homomorphic encryption …