An overview of implementing security and privacy in federated learning
K Hu, S Gong, Q Zhang, C Seng, M **a… - Artificial Intelligence …, 2024 - Springer
Federated learning has received a great deal of research attention recently, with privacy
protection becoming a key factor in the development of artificial intelligence. Federated …
protection becoming a key factor in the development of artificial intelligence. Federated …
The impact of adversarial attacks on federated learning: A survey
Federated learning (FL) has emerged as a powerful machine learning technique that
enables the development of models from decentralized data sources. However, the …
enables the development of models from decentralized data sources. However, the …
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 …
Survey on federated learning threats: Concepts, taxonomy on attacks and defences, experimental study and challenges
Federated learning is a machine learning paradigm that emerges as a solution to the privacy-
preservation demands in artificial intelligence. As machine learning, federated learning is …
preservation demands in artificial intelligence. As machine learning, federated learning is …
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) …
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 …
A review of secure federated learning: privacy leakage threats, protection technologies, challenges and future directions
L Ge, H Li, X Wang, Z Wang - Neurocomputing, 2023 - Elsevier
Advances in the new generation of Internet of Things (IoT) technology are propelling the
growth of intelligent industrial applications worldwide. Simultaneously, widespread adoption …
growth of intelligent industrial applications worldwide. Simultaneously, widespread adoption …
[HTML][HTML] A survey of security strategies in federated learning: Defending models, data, and privacy
Federated Learning (FL) has emerged as a transformative paradigm in machine learning,
enabling decentralized model training across multiple devices while preserving data …
enabling decentralized model training across multiple devices while preserving data …
Fairness and privacy preserving in federated learning: A survey
Federated Learning (FL) is an increasingly popular form of distributed machine learning that
addresses privacy concerns by allowing participants to collaboratively train machine …
addresses privacy concerns by allowing participants to collaboratively train machine …
A systematic review of federated learning from clients' perspective: challenges and solutions
Federated learning (FL) is a machine learning approach that decentralizes data and its
processing by allowing clients to train intermediate models on their devices with locally …
processing by allowing clients to train intermediate models on their devices with locally …