The invention discloses a data asset transaction
system and method based on
federated learning, a trusted execution environment and related
noise differential privacy, and belongs to the technical field of
data security and privacy calculation. The
system comprises a front-end data holding node, a coordination
server, a third-party TEE computing node, a query
payment transaction terminal and a personal terminal, the front-end data holding node is used for executing data preprocessing,
feature extraction and
encryption operations, and the coordination
server is used for executing
network topology construction,
covariance optimization, security aggregation and block chain evidence storage operations. The third-party TEE computing node is used for remote
authentication, compliance examination and privacy enhancement computing operation, the query
payment transaction terminal is used for executing demand
encryption and result display operation, and the personal terminal is used for data contribution and income receiving operation. According to the method, federal learning and related
noise differential privacy are fused,
privacy protection and
noise cooperative counteracting are realized, the model accuracy is improved, and a transaction
system in which data can be invisible is constructed.