GCP Professional Cloud Security Engineer Practice Question
Your company is preparing to share a BigQuery dataset that contains an E.164-formatted phone_number column (for example, "+14155551234") with an external analytics partner. The partner only needs the last four digits for grouping, and compliance policy requires that every preceding character be replaced by a single, repeated masking symbol so that records appear like "+########1234". You will run a one-time Cloud DLP job to de-identify the column and leave all other fields untouched. Which transformation should you configure to meet the requirement with the least implementation effort?
Numeric bucketing transformation that replaces phone numbers with predefined range buckets.
Character masking transformation configured to mask all but the last four characters of PHONE_NUMBER, using "#" as the masking symbol and reverse_order enabled.
Deterministic cryptographic transformation that encrypts the phone numbers with a customer-managed key and uses surrogate annotations.
Redaction transformation that removes values identified as PHONE_NUMBER.
Cloud DLP's character masking transformation is designed to replace each detected character with a chosen masking symbol while optionally preserving a specified number of trailing (or leading) characters. By setting a masking_character such as "#", configuring number_to_mask to cover all but the final four characters, and enabling reverse_order so masking starts from the beginning of the value, you produce strings like "+########1234" that keep their original length and reveal only the last four digits.
Redaction deletes the entire field, eliminating the final digits the partner needs. Crypto-deterministic encryption and format-preserving options create pseudorandom substitutes rather than a uniform masking symbol and require key management. Bucketing converts values into ranges, not masked strings. Therefore, character masking is the simplest and correct choice.
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