These technologies employ various techniques to safeguard data. Some of the key methods include:
- Data Anonymization: Removing or altering identifying information from datasets to prevent the identification of individuals. - Homomorphic Encryption: Allows computations to be performed on encrypted data without needing to decrypt it, ensuring data privacy throughout the process. - Federated Learning: Enables machine learning models to be trained across multiple decentralized devices or servers holding local data samples, without exchanging the data itself. - Differential Privacy: Adds noise to data to mask the identity of individuals while still allowing aggregate data analysis.
