Differential Privacy (EN)
ConceptMathematical concept that protects privacy in data analysis
Data flow in Differential Privacy
flowchart LR A[Original data] --> B[Additive noise] B --> C[Differentially private result] C --> D[Publication/Analysis]
In context
- Typically used together with Federated Learning
- Related to: K-Anonymity, L-Diversity, T-Closeness
- Example use: Google RAPPOR, Apple Differential Privacy