AAISM: Advanced in AI Security Management

Removing private data from training datasets eliminates the sensitive attributes an attacker could infer from a trained model. Federated learning keeps raw data local, but its model updates can still leak local information through inference attacks unless additional controls, such as differential privacy and secure aggregation, are applied.