Medical data joint learning system and method based on trusted computing and privacy protection

Abstract

The invention relates to a medical data joint learning system and method based on trusted computing and privacy protection. A joint learning center control layer receives non-sensitive meta-information uploaded by a data contributor through a data contributor management layer of a data node where the joint learning center control layer is located for filing, and original data is locally registered, stored and subjected to isolation calculation; and the joint learning center control layer processes a joint learning request initiated by the data miner through the data miner interaction layer, summarizes insensitive intermediate results obtained by performing local isolation calculation on the data nodes based on the original data in a safe calculation area, and returns a final joint learningresult to the data miner interaction layer. The invention provides a whole set of service system based on medical big data security sharing, trusted computing, deep mining, authority authentication and multi-platform joint learning, and solves the problems of scattered, single and incomplete medical data privacy protection and data mining at the present stage.

Description

technical field [0001] The invention relates to safe sharing of medical big data, credible mining and privacy security protection. Specifically, it refers to a medical big data joint learning system and method based on trusted computing and privacy protection. Background technique [0002] The existing medical big data search, sharing, and data mining services are still in the immature stage, lacking in-depth and credible mining of data, authority certification, and systematic standards and protection measures have not yet been formed. Strict laws and lack of protection systems and standards have caused a large number of medical data owners such as hospitals and medical research institutions to be unwilling or afraid to share their data resources, which has seriously affected the rapid progress and development of medical disciplines under the trend of Internet big data. Development, for example, comprehensive diagnosis and analysis of diseases, big data statistical analysis...

AI Technical Summary

Problems solved by technology

[0006] The invention relates to a medical data joint learning system and method based on trusted computing and privacy protection, and provides a complete set of service systems based on medical big data security sharing, trusted computing, deep mining, authority authentication, and multi-platform joint learning. It solves the fragmented, single and incomplete problems of medical data privacy protection and data mining at this stage

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