CCSP Cloud Data Security Practice Question
A company is implementing a DLP strategy to protect PII in cloud storage. They need to discover sensitive data and then apply de-identification transforms. Which THREE de-identification transforms are appropriate for anonymizing PII while maintaining data utility for analytics? (Select THREE.)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Pseudonymisation
Masking, tokenization, and pseudonymisation are de-identification transforms that protect PII while preserving some utility. Masking obscures parts of data (e.g., showing only last four digits). Tokenization replaces with tokens that can be mapped back. Pseudonymisation replaces with consistent pseudonyms that are reversible with additional data. Bucketing groups values into ranges, which can be useful but may reduce utility. Encryption is not considered a de-identification transform in DLP context.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Encryption
Why it's wrong here
Encryption protects data but is not a de-identification transform.
- ✗
Bucketing
Why it's wrong here
Bucketing groups values but is not a direct de-identification transform for PII.
- ✓
Pseudonymisation
Why this is correct
Pseudonymisation replaces with consistent pseudonyms.
- ✓
Tokenization
Why this is correct
Tokenization replaces with tokens that can be used for analytics.
- ✓
Masking
Why this is correct
Masking obscures sensitive data while preserving format.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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