A state-of-the-art survey on solving non-iid data in federated learning
Federated Learning (FL) proposed in recent years has received significant attention from
researchers in that it can enable multiple clients to cooperatively train global models without …
researchers in that it can enable multiple clients to cooperatively train global models without …
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 …
Federated learning for privacy-preserving: A review of PII data analysis in Fintech
There has been tremendous growth in the field of AI and machine learning. The
developments across these fields have resulted in a considerable increase in other FinTech …
developments across these fields have resulted in a considerable increase in other FinTech …
Differential privacy for industrial internet of things: Opportunities, applications, and challenges
The development of Internet of Things (IoT) brings new changes to various fields.
Particularly, industrial IoT (IIoT) is promoting a new round of industrial revolution. With more …
Particularly, industrial IoT (IIoT) is promoting a new round of industrial revolution. With more …
Federated learning for 6G-enabled secure communication systems: a comprehensive survey
Abstract Machine learning (ML) and Deep learning (DL) models are popular in many areas,
from business, medicine, industries, healthcare, transportation, smart cities, and many more …
from business, medicine, industries, healthcare, transportation, smart cities, and many more …
A survey of trustworthy federated learning: Issues, solutions, and challenges
Trustworthy artificial intelligence (TAI) has proven invaluable in curbing potential negative
repercussions tied to AI applications. Within the TAI spectrum, federated learning (FL) …
repercussions tied to AI applications. Within the TAI spectrum, federated learning (FL) …
Applications of distributed machine learning for the Internet-of-Things: A comprehensive survey
The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
Distributed few-shot learning for intelligent recognition of communication jamming
Effective recognition of communication jamming is of vital importance in improving wireless
communication system's anti-jamming capability. Motivated by the major challenges that the …
communication system's anti-jamming capability. Motivated by the major challenges that the …
A comprehensive survey on local differential privacy toward data statistics and analysis
T Wang, X Zhang, J Feng, X Yang - Sensors, 2020 - mdpi.com
Collecting and analyzing massive data generated from smart devices have become
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …
increasingly pervasive in crowdsensing, which are the building blocks for data-driven …
3dfed: Adaptive and extensible framework for covert backdoor attack in federated learning
Federated Learning (FL), the de-facto distributed machine learning paradigm that locally
trains datasets at individual devices, is vulnerable to backdoor model poisoning attacks. By …
trains datasets at individual devices, is vulnerable to backdoor model poisoning attacks. By …