AWS clean-rooms documentation change
Summary
Removed warning about synthetic data potentially containing PII, kept mitigation recommendations
Security assessment
Simplifies documentation by removing a caveat about PII in synthetic data while retaining mitigation advice. No evidence of addressing a specific security issue.
Diff
diff --git a/clean-rooms/latest/userguide/create-ml-input-channel.md b/clean-rooms/latest/userguide/create-ml-input-channel.md index efed52597..087bdeda3 100644 --- a//clean-rooms/latest/userguide/create-ml-input-channel.md +++ b//clean-rooms/latest/userguide/create-ml-input-channel.md @@ -73 +73 @@ Synthetic data generation protects against inferring individual attributes wheth -Synthetic data generation protects against inferring individual attributes whether specific individuals are present in the original dataset or learning attributes of those individuals are present. However, it doesn't prevent literal values from the original dataset, including personally identifiable information (PII) from appearing in the synthetic dataset. We recommend avoiding values in the input dataset that are associated with only one data subject because these may re-identify a data subject. For example, if only one user lives in a zip code, the presence of that zip code in the synthetic dataset would confirm that user was in the original dataset. Techniques like truncating high precision values or replacing uncommon catalogues with _other_ can be used to mitigate this risk. These transformations can be part of the query used to create the ML input channel. +We recommend avoiding values in the input dataset that are associated with only one data subject because these may re-identify a data subject. For example, if only one user lives in a zip code, the presence of that zip code in the synthetic dataset would confirm that user was in the original dataset. Techniques like truncating high precision values or replacing uncommon catalogues with _other_ can be used to mitigate this risk. These transformations can be part of the query used to create the ML input channel.