Blockchain-based Federated Learning with SMPC Model Verification Against Poisoning Attack for Healthcare Systems. (arXiv:2304.13360v1 [cs.CR])

Due to the rising awareness of privacy and security in machine learning
applications, federated learning (FL) has received widespread attention and
applied to several areas, e.g., intelligence healthcare systems, IoT-based
industries, and smart cities. FL enables clients to train a global model
collaboratively without accessing their local training data. However, the
current FL schemes are vulnerable to adversarial attacks. Its architecture
makes detecting and defending against malicious model updates difficult. In
addition, most recent studies to detect FL from malicious …

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