Journal
2022 IEEE INTERNATIONAL CONFERENCE ON BLOCKCHAIN (BLOCKCHAIN 2022)
Volume -, Issue -, Pages 194-201Publisher
IEEE COMPUTER SOC
DOI: 10.1109/Blockchain55522.2022.00034
Keywords
federated learning; blockchain; off-chain computations; verifiability; zero-knowledge proofs; zokrates
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Funding
- Austrian Federal Ministry for Digital and Economic Affairs
- National Foundation for Research, Technology and Development
- Christian Doppler Research Association
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This paper introduces the use of zero-knowledge proofs as an alternative to incentive and penalty mechanisms in blockchain-based federated learning. By utilizing off-chain computations and verification on the blockchain, the correctness of the learning processes can be ensured.
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 parameters 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.
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