Shielding Collaborative Learning: Mitigating Poisoning Attacks Through Client-Side Detection
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2020.2986205
Abstract: Collaborative learning allows multiple clients to train a joint model without sharing their data with each other. Each client performs training locally and then submits the model updates to a central server for aggregation. Since… read more here.
Keywords: detection; client side; poisoning attacks; collaborative learning ... See more keywords
FLCert: Provably Secure Federated Learning Against Poisoning Attacks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2022.3212174
Abstract: Due to its distributed nature, federated learning is vulnerable to poisoning attacks, in which malicious clients poison the training process via manipulating their local training data and/or local model updates sent to the cloud server,… read more here.
Keywords: provably secure; flcert provably; federated learning; secure federated ... See more keywords
RobustFL: Robust Federated Learning Against Poisoning Attacks in Industrial IoT Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2021.3132954
Abstract: Industrial Internet of Things (IIoT) systems are key enabling infrastructures that sustain the functioning of production and manufacturing. To satisfy the intelligence demands, federated learning has been envisioned as a promising technique for IIoT applications… read more here.
Keywords: robust federated; federated learning; learning poisoning; model ... See more keywords
Data Poisoning Attacks in Internet-of-Vehicle Networks: Taxonomy, State-of-The-Art, and Future Directions
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2022.3198481
Abstract: With the unprecedented development of deep learning, autonomous vehicles (AVs) have achieved tremendous progress nowadays. However, AV supported by DNN models is vulnerable to data poisoning attacks, hindering the large-scale application of autonomous driving. For… read more here.
Keywords: attacks defenses; data poisoning; state art; poisoning attacks ... See more keywords
Toward Robust Hierarchical Federated Learning in Internet of Vehicles
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Intelligent Transportation Systems"
DOI: 10.1109/tits.2023.3243003
Abstract: The rapid growth of the Internet of Vehicles (IoV) paradigm sparks the generation of large volumes of distributed data at vehicles, which can be harnessed to build models for intelligent applications. Federated learning has recently… read more here.
Keywords: aggregation; federated learning; robust hierarchical; internet vehicles ... See more keywords