Building trusted federated learning: Key technologies and challenges
Federated learning (FL) provides convenience for cross-domain machine learning
applications and has been widely studied. However, the original FL is still vulnerable to …
applications and has been widely studied. However, the original FL is still vulnerable to …
Sentinel: An Aggregation Function to Secure Decentralized Federated Learning
C Feng, AH Celdrán, J Baltensperger… - arXiv preprint arXiv …, 2023 - arxiv.org
The rapid integration of Federated Learning (FL) into networking encompasses various
aspects such as network management, quality of service, and cybersecurity while preserving …
aspects such as network management, quality of service, and cybersecurity while preserving …
Federated learning attacks revisited: A critical discussion of gaps, assumptions, and evaluation setups
Deep learning pervades heavy data-driven disciplines in research and development. The
Internet of Things and sensor systems, which enable smart environments and services, are …
Internet of Things and sensor systems, which enable smart environments and services, are …
CONTRA: Defending Against Poisoning Attacks in Federated Learning
Federated learning (FL) is an emerging machine learning paradigm. With FL, distributed
data owners aggregate their model updates to train a shared deep neural network …
data owners aggregate their model updates to train a shared deep neural network …
A survey of trustworthy federated learning with perspectives on security, robustness and privacy
Trustworthy artificial intelligence (AI) technology has revolutionized daily life and greatly
benefited human society. Among various AI technologies, Federated Learning (FL) stands …
benefited human society. Among various AI technologies, Federated Learning (FL) stands …
[HTML][HTML] Security of federated learning with IoT systems: Issues, limitations, challenges, and solutions
Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …
reputation for not only building Machine Learning (ML) models that rely on distributed …
Trusted decentralized federated learning
A Gholami, N Torkzaban… - 2022 IEEE 19th Annual …, 2022 - ieeexplore.ieee.org
Federated learning (FL) has received significant attention from both academia and industry,
as an emerging paradigm for building machine learning models in a communication-efficient …
as an emerging paradigm for building machine learning models in a communication-efficient …
Security and privacy threats to federated learning: Issues, methods, and challenges
Federated learning (FL) has nourished a promising method for data silos, which enables
multiple participants to construct a joint model collaboratively without centralizing data. The …
multiple participants to construct a joint model collaboratively without centralizing data. The …
Federated learning vulnerabilities, threats and defenses: A systematic review and future directions
S Almutairi, A Barnawi - Internet of Things, 2023 - Elsevier
Today, a broad range of items, ranging from smartphones to smart cars are connected
together via the Internet, also known as the Internet of Things (IoT). The IoT is powered by …
together via the Internet, also known as the Internet of Things (IoT). The IoT is powered by …
Shielding federated learning: A new attack approach and its defense
Federated learning (FL) is a newly emerging distributed learning framework that is
communication-efficient with user privacy guarantee. Wireless end-user devices can …
communication-efficient with user privacy guarantee. Wireless end-user devices can …