MLA-C01 Question 106
Single answerYou are designing a machine learning pipeline to process sensitive customer data, including personally identifiable information (PII). To comply with data privacy regulations, you need to ensure the data is anonymized before it is stored for training purposes. Which of the following approaches would best meet this requirement?
- A
Use Amazon Macie to automatically redact sensitive information in the dataset before storing it.
- B
Apply irreversible hash functions (e.g., SHA-256) to PII fields to anonymize them.
- C
Encrypt the PII fields using AWS KMS and store the encryption keys securely.
- D
Mask PII fields using random placeholder values before using the data for training.
Show answer and explanation
Correct answer: B
Explanation
To comply with data privacy regulations, anonymization of PII ensures that the data cannot be traced back to individuals. Using an irreversible hash function like SHA-256 achieves this by transforming the data into a fixed-length string that cannot be reversed, thereby meeting the requirement for anonymization. Other options like encryption and masking do not provide the same level of assurance since they can be reversed or are not truly secure.
- A. Incorrect.
Amazon Macie is a service that helps you identify and classify sensitive data, but it does not perform anonymization. It would be useful for detecting PII but not for anonymizing it.
- B. Correct.
Applying irreversible hash functions to PII fields ensures the data cannot be traced back to the original values, making it an ideal method for anonymization.
- C. Incorrect.
Encrypting PII fields protects the data at rest or in transit but does not anonymize it. Encrypted data can still be decrypted, which does not meet the requirement for anonymization.
- D. Incorrect.
Masking PII fields with random placeholder values can obscure the data temporarily, but it is not a secure or irreversible method for anonymization.