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?

Real Exam

Apply k-anonymization to datasets before AI training, ensuring that each record is indistinguishable from at least k-1 other records concerning sensitive attributes.

15.1%

Encrypt data using homomorphic encryption techniques, allowing AI models to be trained on encrypted data without ever accessing plaintext information.

25.6%

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.

47.7%

Use simple data masking techniques, replacing sensitive information with generic placeholders.

11.6%

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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?