Privacy
Exposure Reduction
Techniques that reduce how much real personal data is collected, shared or retained, without proving a bound on what remains.
1 subcategory • 6 techniques
Techniques
6 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| GAN-Based Tabular Synthetic Data | Algorithmic | Architecture/neural Networks/generative/gan Architecture/neural Networks/generative/vae +3 | Tabular | GAN-based tabular synthetic data generation trains a generative model on a real table, then samples new rows from it to... | ||
| Sequential CART Synthesis | Algorithmic | Architecture/model Agnostic Requirements/black Box | Tabular | Sequential CART synthesis creates an artificial copy of a confidential microdata set (records about individual people or... | ||
| Federated Learning | Algorithmic | Architecture/linear Models Architecture/neural Networks +4 | Any | Federated learning trains one shared model across several parties, such as phones or hospitals, without collecting their... | ||
| Machine Unlearning | Algorithmic | Architecture/model Agnostic Architecture/neural Networks +2 | Any | Machine unlearning removes the influence of specific training records from a trained model, so that the model behaves as... | ||
| k-Anonymity | Algorithmic | Architecture/model Agnostic Requirements/black Box | Tabular | k-Anonymity is a property that a table of real records about people can be made to satisfy before it is released or... | ||
| PII Detection and Redaction in Training Text | Algorithmic | Architecture/model Agnostic Architecture/neural Networks/transformer/llm +1 | Text | PII detection and redaction finds personally identifiable information (PII), such as names, email addresses, phone... |
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