Question

Difficulty: MediumData Governance, Classification, and Privacy Controls

A biotechnology organization needs to share clinical trial data with an external analytics firm. To comply with privacy requirements, the security team must replace sensitive patient identifiers with non-sensitive placeholder values. The system must maintain an internal mapping database that allows authorized internal personnel to reverse the process when necessary, while ensuring external analysts cannot mathematically derive original identities from the placeholders alone. Which of the following privacy-enhancing techniques should the organization implement?

  1. TokenizationAnswer
  2. B
    Anonymization
  3. C
    Dynamic data masking
  4. D
    Symmetric stream cipher encryption

Answer

Tokenization is the correct privacy control because it replaces sensitive values with random surrogate tokens backed by an internal lookup vault, enabling reversible mapping for authorized personnel without exposing algorithmic relationship vectors to third parties.
Tokenization is the correct mechanism because it substitutes sensitive values with non-sensitive identifiers (tokens) while retaining the original data in a separate, highly secured token vault database. This allows internal authorized systems to map tokens back to original entries while preventing external parties from mathematically deriving the original data.

Step-by-Step Solution

1
Analyze the operational requirements for handling patient data.
Identified two key needs: replacing direct identifiers for external sharing and maintaining a reversible mapping mechanism restricted to internal use.
Privacy compliance requires minimizing exposure while preserving operational utility for safety tracking.
2
Evaluate privacy-enhancing technology characteristics against the requirement for authorized reversibility via a mapping table.
Tokenization utilizes a database lookup mechanism (token vault) rather than a mathematical key transformation, satisfying both the non-derivability constraint and the reversible mapping constraint.
Unlike permanent sanitization or mathematical ciphering, tokenization explicitly decouples original data from surrogate values via centralized storage.

Key Concept

Tokenization vs. Anonymization and Masking in Data Privacy Management
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