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Recently, blockchain-based federated learning (BFL) has attracted intensive research attention due to that the training process is auditable and the architecture is serverless avoiding the single point failure of the parameter server in vanilla federated learning (VFL) However, this adoption has been accompanied by a surge in cryptocurrency fraud, causing significant losses to financial organizations and individuals

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