Data and model poisoning backdoor attacks on wireless federated learning, and the defense mechanisms: A comprehensive survey
Due to the greatly improved capabilities of devices, massive data, and increasing concern
about data privacy, Federated Learning (FL) has been increasingly considered for …
about data privacy, Federated Learning (FL) has been increasingly considered for …
Emerging trends in federated learning: From model fusion to federated x learning
Federated learning is a new learning paradigm that decouples data collection and model
training via multi-party computation and model aggregation. As a flexible learning setting …
training via multi-party computation and model aggregation. As a flexible learning setting …
Multitentacle federated learning over software-defined industrial internet of things against adaptive poisoning attacks
G Li, J Wu, S Li, W Yang, C Li - IEEE Transactions on Industrial …, 2022 - ieeexplore.ieee.org
Software-defined industrial Internet of things (SD-IIoT) exploits federated learning to process
the sensitive data at edges, while adaptive poisoning attacks threat the security of SD-IIoT …
the sensitive data at edges, while adaptive poisoning attacks threat the security of SD-IIoT …
SIDS: A federated learning approach for intrusion detection in IoT using Social Internet of Things
Abstract The Internet of Things (IoT) ecosystem needs Intrusion Detection Systems (IDS) to
mitigate cyberattacks and exploit security vulnerabilities. Over the past years, utilizing …
mitigate cyberattacks and exploit security vulnerabilities. Over the past years, utilizing …
FedCL: Federated contrastive learning for multi-center medical image classification
Z Liu, F Wu, Y Wang, M Yang, X Pan - Pattern Recognition, 2023 - Elsevier
Federated learning, which allows distributed medical institutions to train a shared deep
learning model with privacy protection, has become increasingly popular recently. However …
learning model with privacy protection, has become increasingly popular recently. However …
Toward personalized federated learning via group collaboration in IIoT
Despite the rapid growth of successful examples of Federated Learning (FL), it faces the
heterogeneity of data, models, and devices in emerging applications of Industrial Internet of …
heterogeneity of data, models, and devices in emerging applications of Industrial Internet of …
Revisiting personalized federated learning: Robustness against backdoor attacks
In this work, besides improving prediction accuracy, we study whether personalization could
bring robustness benefits to backdoor attacks. We conduct the first study of backdoor attacks …
bring robustness benefits to backdoor attacks. We conduct the first study of backdoor attacks …
Decentralized learning in healthcare: a review of emerging techniques
Recent developments in deep learning have contributed to numerous success stories in
healthcare. The performance of a deep learning model generally improves with the size of …
healthcare. The performance of a deep learning model generally improves with the size of …
FedAWR: An interactive federated active learning framework for air writing recognition
The rapid development of technology such as virtual reality and augmented reality, coupled
with the reduced direct contact due to the COVID-19 pandemic, has led to the emergence of …
with the reduced direct contact due to the COVID-19 pandemic, has led to the emergence of …