Blockchain-based Federated Learning with Secure Aggregation in Trusted Execution Environment for Internet-of-Things. (arXiv:2304.12889v1 [cs.CR])

This paper proposes a blockchain-based Federated Learning (FL) framework with
Intel Software Guard Extension (SGX)-based Trusted Execution Environment (TEE)
to securely aggregate local models in Industrial Internet-of-Things (IIoTs). In
FL, local models can be tampered with by attackers. Hence, a global model
generated from the tampered local models can be erroneous. Therefore, the
proposed framework leverages a blockchain network for secure model aggregation.
Each blockchain node hosts an SGX-enabled processor that securely performs the
FL-based aggregation tasks to generate a …

aggregation attackers blockchain blockchain network environment extension federated learning framework generated global guard industrial intel internet local network node nodes processor sgx software things trusted execution environment verify