Fostering trustworthiness of federated learning ecosystem through realistic scenarios
The present study thoroughly evaluates the most common blocking challenges faced by the
federated learning (FL) ecosystem and analyzes existing state-of-the-art solutions. A system …
federated learning (FL) ecosystem and analyzes existing state-of-the-art solutions. A system …
Analyzing the robustness of decentralized horizontal and vertical federated learning architectures in a non-IID scenario
PM Sánchez Sánchez, A Huertas Celdrán… - Applied …, 2024 - Springer
Federated learning (FL) enables participants to collaboratively train machine and deep
learning models while safeguarding data privacy. However, the FL paradigm still has …
learning models while safeguarding data privacy. However, the FL paradigm still has …
A survey on security and privacy of federated learning
Federated learning (FL) is a new breed of Artificial Intelligence (AI) that builds upon
decentralized data and training that brings learning to the edge or directly on-device. FL is a …
decentralized data and training that brings learning to the edge or directly on-device. FL is a …
Security of federated learning in 6G era: A review on conceptual techniques and software platforms used for research and analysis
Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm enabling
multiple parties to train a model collaboratively without sharing their data. With the upcoming …
multiple parties to train a model collaboratively without sharing their data. With the upcoming …
[PDF][PDF] A Survey on Securing Federated Learning: Analysis of Applications, Attacks, Challenges, and Trends.
The growth of data generation capabilities, facilitated by advancements in communication
and computation technologies, as well as the rise of the Internet of Things (IoT), results in …
and computation technologies, as well as the rise of the Internet of Things (IoT), results in …
Threats, attacks and defenses to federated learning: issues, taxonomy and perspectives
Abstract Empirical attacks on Federated Learning (FL) systems indicate that FL is fraught
with numerous attack surfaces throughout the FL execution. These attacks can not only …
with numerous attack surfaces throughout the FL execution. These attacks can not only …
Blockchained Trustable Federated Learning Utilizing Voting Accountability for Malicious Actor Mitigation
B Stanley, SG Lee, EN Witanto - Applied Sciences, 2023 - mdpi.com
The federated learning (FL) approach in machine learning preserves user privacy during
data collection. However, traditional FL schemes still rely on a centralized server, making …
data collection. However, traditional FL schemes still rely on a centralized server, making …
Securing Federated Learning: A Security Analysis on Applications, Attacks, Challenges, and Trends
The growth of data generation capabilities, facilitated by advancements in communication
and computation technologies, as well as the rise of the Internet of Things (IoT), results in …
and computation technologies, as well as the rise of the Internet of Things (IoT), results in …
Security in Federated Learning Enabled 6g Era: A Review on Conceptual Techniques and Software Platforms Used for Research and Analysis
Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm that enables
multiple parties to collaboratively train a model without sharing their data. With the upcoming …
multiple parties to collaboratively train a model without sharing their data. With the upcoming …
Backdoor attacks and defenses in federated learning: Survey, challenges and future research directions
Federated learning (FL) is an approach within the realm of machine learning (ML) that
allows the use of distributed data without compromising personal privacy. In FL, it becomes …
allows the use of distributed data without compromising personal privacy. In FL, it becomes …