GCP Professional Cloud Security Engineer Practice Question
Your security team must export customer chat transcripts stored in a BigQuery table to an external analytics partner for sentiment analysis. The transcripts occasionally contain payment card numbers and Social Security numbers. The partner does not need to see any portion of those numbers and you want to ensure the sensitive tokens are completely removed rather than obscured, encrypted, or replaced with reversible surrogates. Which Sensitive Data Protection transformation should you configure in the Cloud DLP job to meet this requirement?
Redaction is the transformation that removes the matched sensitive data from the payload entirely-typically replacing it with an empty string or a user-supplied replacement. Because the partner must not see any part of the card or SSN values and re-identification will never be required, redaction is the most appropriate choice. Masking would leave the length of the value visible, tokenization would create reversible surrogates, and format-preserving encryption would still allow the ciphertext to be decrypted later, so none of those meet the requirement of complete removal.
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What is Cloud DLP in GCP?
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How does redaction work in Cloud DLP?
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What are the differences between redaction and masking in GCP DLP?
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What is Cloud DLP?
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What is redaction and how does it differ from masking?
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When should you choose redaction over other Cloud DLP transformations like tokenization?
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GCP Professional Cloud Security Engineer
Ensuring data protection
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