Machine learning task distribution method, device and system based on block chain

Abstract

The embodiment of the invention provides a machine learning task distribution method, device and system based on a block chain, relates to the technical field of block chains, and can better use the block chain technology to realize self-consistent operation of the machine learning task distribution system based on the block chain. The machine learning task distribution method based on the block chain is applied to a machine learning task distribution system based on the block chain. The machine learning task distribution system based on the block chain comprises a block chain server node and a plurality of user nodes, wherein the first user node selects a second user node according to the credit score of the second user node, the first user node sends training task data to the second user node, and the second user node performs task model training according to the training task data to generate a task model; the third user node tests the task model, and the blockchain server node pays a first predetermined number of tokens to the second user node; the first user node generates and broadcasts a block.

Description

technical field [0001] The present application relates to the technical field of blockchain, in particular to a blockchain-based machine learning task distribution method, device and system. Background technique [0002] Machine learning means training a large amount of task data to produce a suitable task model for subsequent use. Among them, the blockchain-based machine learning task distribution system can publish the task data in machine learning to different users in the machine learning task distribution system, so that different users can process synchronously and jointly train the task model. [0003] However, directly publishing machine learning task data in the machine learning task distribution system will inevitably lead to the leakage of some or all task data. If the leaked task data is analyzed and sorted, the information of the user who released the task data will will be leaked. With the leakage of user information, the user's identity will be in an open an...

AI Technical Summary

Problems solved by technology

[0003]However, publishing machine learning task data directly in the machine learning task distribution system will inevitably lead to the leakage of some or all task data. If the leaked task If the data is analyzed and sorted, the information of the user who released the task data will also be leaked

With the leakage of user information, the user's identity will be in an open and transparent environment in the machine learning task distribution system, so the user's activities of publishing task data or task model training in the machine learning task distribution system will be subject to varying degrees of punishment. At the same time, it will cause unfair phenomena in the machine learning task distribution system, and the machine learning task distribution system cannot run self-consistently

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