TPE-BFL: Training Parameter Encryption scheme for Blockchain based Federated Learning system

Fanfan shen

Abstract:

Blockchain technology plays a pivotal role in addressing the single point of failure issues in federated
learning systems, due to the immutable nature and decentralized architecture. However, traditional blockchainbased federated learning systems still face privacy and security challenges when transmitting training model
parameters to individual nodes. Malicious nodes within the system can exploit this process to steal parameters
and extract sensitive information, leading to data leakage. To address this problem, we propose a Training
Parameter Encryption scheme for Blockchain based Federated Learning system (TPE-BFL). In TPE-BFL, the
training parameters of the system model are encrypted using the paillier algorithm with the property of
addition homomorphism. This encryption mechanism is integrated into the workflows of three distinct roles
within the system: workers, validators, and miners. (1) Workers utilize the paillier encryption algorithm to
encrypt training parameters for local training models. (2) Validators decrypt received encrypted training
parameters using private keys to verify their validity. (3) Miners receive cryptographic training parameters
from validators, validate them, and generate blocks for subsequent global model updates. By implementing
the TPE-BFL mechanism, we not only preserve the immutability and decentralization advantages of blockchain
technology but also significantly enhance the privacy protection capabilities during data transmission in
federated learning systems. In order to verify the security of TPE-BFL, we leverage the semantic security
inherent in the Paillier encryption algorithm to theoretically substantiate the security of our system. In addition,
we conducted a large number of experiments on real-world data to prove the validity of our proposed TPE-BFL,
and when 15% of malicious devices are present, TPE-BFL achieve 92% model accuracy, a 5% improvement
over the blockchain-based decentralized FL framework (VBFL)