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Advancing blockchain-based federated learning through verifiable off-chain computations
Publikationstyp
Conference Paper
Date Issued
2022
Sprache
English
Institut
Start Page
194
End Page
201
Citation
5th IEEE International Conference on Blockchain, Blockchain 2022: 194-201 (2022)
Contribution to Conference
Publisher DOI
Scopus ID
Publisher
IEEE
Federated learning may be subject to both global aggregation attacks and distributed poisoning attacks. Blockchain technology along with incentive and penalty mechanisms have been suggested to counter these. In this paper, we explore verifiable off-chain computations using zero-knowledge proofs as an alternative to incentive and penalty mechanisms in blockchain-based federated learning. In our solution, learning nodes, in addition to their computational duties, act as off-chain provers submitting proofs to attest computational correctness of param-eters that can be verified on the blockchain. We demonstrate and evaluate our solution through a health monitoring use case and proof-of-concept implementation leveraging the ZoKrates language and tools for smart contract-based on-chain model management. Our research introduces verifiability of correctness of learning processes, thus advancing blockchain-based federated learning.
Subjects
MLE@TUHH
DDC Class
620: Ingenieurwissenschaften