Golden Grain: Building a Secure and Decentralized Model Marketplace for MLaaS
Jiasi Weng, Jian Weng, Chengjun Cai, Hongwei Huang, Cong Wang

TL;DR
Golden Grain is a blockchain-based decentralized marketplace for ML models that incentivizes sharing through transparent benchmarking and secure off-chain interactions, facilitating fair model trading for MLaaS providers.
Contribution
The paper introduces a novel blockchain-enabled model marketplace with a secure off-chain benchmarking protocol to motivate model sharing among developers and MLaaS providers.
Findings
Prototype implementation on Ethereum demonstrates practical performance.
Secure off-chain benchmarking reduces blockchain overhead.
Transparent pricing based on authentic model performance.
Abstract
ML-as-a-service (MLaaS) becomes increasingly popular and revolutionizes the lives of people. A natural requirement for MLaaS is, however, to provide highly accurate prediction services. To achieve this, current MLaaS systems integrate and combine multiple well-trained models in their services. Yet, in reality, there is no easy way for MLaaS providers, especially for startups, to collect sufficiently well-trained models from individual developers, due to the lack of incentives. In this paper, we aim to fill this gap by building up a model marketplace, called as Golden Grain, to facilitate model sharing, which enforces the fair model-money swapping process between individual developers and MLaaS providers. Specifically, we deploy the swapping process on the blockchain, and further introduce a blockchain-empowered model benchmarking process for transparently determining the model prices…
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Taxonomy
TopicsBlockchain Technology Applications and Security · Cloud Data Security Solutions · Cryptography and Data Security
