Data-Agnostic Model Poisoning Against Federated Learning: A Graph Autoencoder Approach

Li, Kai; Zheng, Jingjing; Yuan, Xin; Ni, Wei; Akan, Ozgur B.; Poor, H. Vincent

doi:10.1109/tifs.2024.3362147

IEEE Trans.Inform.Forensic Secur.

2024

DOI: 10.1109/tifs.2024.3362147

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Data-Agnostic Model Poisoning Against Federated Learning: A Graph Autoencoder Approach

Kai Li,

Jingjing Zheng,

Xin Yuan

et al.

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Low dimensional secure federated learning framework against poisoning attacks

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A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and Ways Forward

Majeed,

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2024

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Optimizing Federated Learning on TinyML Devices for Privacy Protection and Energy Efficiency in IoT Networks

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Data-Agnostic Model Poisoning Against Federated Learning: A Graph Autoencoder Approach

Cited by 3 publications

References 52 publications

Low dimensional secure federated learning framework against poisoning attacks

Low dimensional secure federated learning framework against poisoning attacks

A Multifaceted Survey on Federated Learning: Fundamentals, Paradigm Shifts, Practical Issues, Recent Developments, Partnerships, Trade-Offs, Trustworthiness, and Ways Forward

Optimizing Federated Learning on TinyML Devices for Privacy Protection and Energy Efficiency in IoT Networks

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