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CCSP · Question #324

Although indirect identifiers cannot alone point to an individual, the more of them known can lead to a specific identity. Which strategy can be used to avoid such a connection being made? Response:

The correct answer is B. Anonymization. Anonymization is the process of removing or modifying personally identifiable information (PII) from data sets so that individuals cannot be directly or indirectly identified, even by combining multiple indirect identifiers.

Submitted by paula_co· Apr 18, 2026Cloud Data Security

Question

Although indirect identifiers cannot alone point to an individual, the more of them known can lead to a specific identity. Which strategy can be used to avoid such a connection being made? Response:

Options

  • AMasking
  • BAnonymization
  • CObfuscation
  • DEncryption

How the community answered

(25 responses)
  • A
    4% (1)
  • B
    88% (22)
  • C
    4% (1)
  • D
    4% (1)

Why each option

Anonymization is the process of removing or modifying personally identifiable information (PII) from data sets so that individuals cannot be directly or indirectly identified, even by combining multiple indirect identifiers.

AMasking

Data masking replaces sensitive data with non-sensitive but realistic data, primarily for testing or training, and while it protects original data, it might not fully prevent re-identification through indirect identifiers if the masking is not sufficiently robust.

BAnonymizationCorrect

Anonymization involves transforming data so that individual records cannot be linked back to the original person, even when combining multiple indirect identifiers. This process aims to prevent re-identification, making it suitable for situations where preventing a connection to a specific identity from indirect data is crucial.

CObfuscation

Obfuscation makes data or code harder to understand but doesn't necessarily remove identifying links, meaning that with enough indirect identifiers, re-identification might still be possible.

DEncryption

Encryption transforms data into an unreadable format but retains the ability to decrypt it back to its original state, thus not preventing re-identification if the key is compromised or the data is decrypted.

Concept tested: Data anonymization for privacy

Source: https://learn.microsoft.com/en-us/azure/architecture/example-scenario/data/highly-secure-data-privacy-platform

Topics

#Data Anonymization#Privacy#Re-identification#Indirect Identifiers

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