FL-Incentivizer: FL-NFT and FL-Tokens for Federated Learning Model Trading and Training

نویسندگان

چکیده

Federated learning (FL) is an on-device distributed scheme that does not require training devices to transfer their data a centralized facility. The goal of federated learn global model over several iterations. It challenging claim ownership rights and commercialize the efficiently transparently. Additionally, incentives need be provided ensure participate in FL process. In this paper, we propose smart contract-based framework called FL-Incentivizer, which relies on custom contracts maintain flow governance process transparent immutable manner. FL-Incentivizer commercializes tokenizes using FL-NFT (FL Non-Fungible Token) based ERC-721 standard. uses ERC-20 compliant FL-Tokens incentivize participating FL. We present system design operational sequence FL-Incentivizer. provide implementation deployment details, complete contract codes, qualitative evaluation After implementing for iteration task, showed OpenSea FL-Token learner MetaMask. FL-NFTs can traded markets such as like other NFTs. While transferred same manner ERC-20-based tokens.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2023

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2023.3235484