Smart contract-based decentralized federated machine learning method, system and storage medium
Active Publication Date: 2021-11-23
BEIJING UNIV OF POSTS & TELECOMM
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Problems solved by technology
The invention focuses on solving the centralization problem of federated machine learning
Based on this decentralization mechanism, decentralized federated machine learning technology is realized, which solves the centralization problem of federated machine learning
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[0052] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the embodiments and accompanying drawings. Here, the exemplary embodiments and descriptions of the present invention are used to explain the present invention, but not to limit the present invention.
[0053] Here, it should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only the structures and / or processing steps closely related to the solution according to the present invention are shown in the drawings, and the related Other details are not relevant to the invention.
[0054] It should be emphasized that the term "comprising / comprising" when used herein refers to the presence of a feature, element, step or component, but does not exclude the presence or addition of one or more other features, elements, steps or components.
[0055] In ord...
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The present invention proposes a decentralized federated machine learning method, system and storage medium based on smart contracts. The method includes an election phase, a purchase phase and a working phase: in the election phase, after the election phase is triggered by the old committee node, the smart contract platform The election parameters are received and recorded from the old committee nodes, the final election parameters are determined based on the received election parameters and election events are notified to each node, the smart contract platform receives the deposit sent by the nodes participating in the election, sorts the participating nodes and determines the new Committee node; in the purchase phase, receive the merged model price sent by multiple new committee nodes, and determine the final merged model price by voting based on the received merged model price, and receive the sub-model submitted by each participating node and the final payment Consolidated model price; used for consensus on the consolidated model in the working phase, which includes at least one round of model validation and merging steps.
Description
technical field [0001] The present invention relates to the technical field of computer software, in particular to a decentralized distributed system, in particular to a decentralized federation machine learning method and system based on smart contracts. Background technique [0002] As digital technology enters a period of rapid development, technologies such as big data and artificial intelligence are leading explosive development, bringing new opportunities for upgrading and reforming traditional models. On the one hand, artificial intelligence algorithms have improved traditional work efficiency; on the other hand, they have also brought new challenges to data and network security. The problem of data islands is one of the key challenges. [0003] The training of intelligent algorithm models requires a large amount of data, but for some private data, such as bank data, medical data, etc., data collection is very difficult. Google proposed federated machine learning in...
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IPC IPC(8): G06Q30/02G06N20/00
CPCG06Q30/0201G06Q30/0206G06Q30/0226G06N20/00
Inventor 杨谈杨超群苗桂田曾庆涛崔毅东雷友珣陈莉萍
Owner BEIJING UNIV OF POSTS & TELECOMM