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When training AI models on sensitive datasets, ensuring data privacy is crucial. Which technique effectively anonymizes data, preserving its utility for AI training while adhering to privacy regulations?
A
Apply k-anonymization to datasets before AI training, ensuring that each record is indistinguishable from at least k-1 other records concerning sensitive attributes.
B
Encrypt data using homomorphic encryption techniques, allowing AI models to be trained on encrypted data without ever accessing plaintext information.
C
Implement differential privacy during the data collection and preprocessing stages, adding noise to the datasets in a way that masks individual contributions but allows for accurate model training.
D
Use simple data masking techniques, replacing sensitive information with generic placeholders.
