$WiMi Hologram Cloud (WIMI.US)$ Homomorphic encryption is a ...

Homomorphic encryption is a special encryption technique that enables computational operations to be performed in an encrypted state without decrypting the data.

By utilizing homomorphic encryption, it is possible to compute and share data in an encrypted state while protecting data privacy and integrity, which is useful for some scenarios involving sensitive data.

Federated learning is a distributed machine learning technique that enables model improvement by allowing multiple participants to train models on their respective local datasets without sharing the original data, and aggregating the learned parameters of these models into a global model.

In data structuring, federated learning can address the issues of data privacy and data security.

The application of homomorphic encryption and federated learning is of great significance in the data structure, which can provide efficient computation and analysis capabilities while protecting user privacy, bringing more possibilities for technology utilization in the technology industry.

This application is expected to play an important role in medical and financial fields, promoting secure data sharing and innovative research, and promoting the continuous development of the big data field.