The invention provides a verifiable training classification model in a mobile communication
system and a classification method of the verifiable training classification model, relates to the technical field of cloud services, designs a cloud edge collaborative classifier training framework capable of protecting privacy, and safely outsourcing time-consuming operation to an ES (Extended
Station) so as to reduce the calculation burden of SMD (Surface
Mount Device) and CS (
Circuit Switching). Meanwhile, the calculation efficiency of classification service can be improved, and the data volume is increased. Secondly, an
algorithm library based on multi-key fully
homomorphic encryption is further designed, and the
algorithm library supports distance and comparison calculation operation of encrypted data. In addition, the
algorithm library can also construct other
privacy protection classifier training services in a modular mode. Finally, a classification method capable of verifying the training classification model in the mobile communication
system is provided, and lightweight integrity
verification is achieved. The SMD only needs to execute a simple
online signature operation, and most of time-consuming offline operations are safely outsourced to an edge service, so that any encrypted aggregated data is ensured not to be replaced or tampered before being decrypted.