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PoCQ: Defending Decentralised Federated Learning Against Model Poisoning and Collusion with Verifiable Evidence
Decentralised federated learning removes the central coordinator but requires participants to establish model update integrity autonomously. Existing frameworks either use inexpensive yet unverifiable proxies, including dataset size and epoch count, or validate updates through retraining, which is c
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