Comparison with Other Privacy-Enhancing Technologies

The following section provides details about synthetic data and other data protection methods.

• Pseudonymization replaces real data with tokens for certain attributes, such as Personally Identifiable Information (PII). However, this method still uses real data, and the analytical value is perfect unless other attributes are tokenized.

• Anonymization reduces the risk of reidentification by transforming quasi-identifiers. However, careful balancing of utility and privacy is needed to minimize the impact on downstream usage.

• Synthetic Data closely resembles real data. It does not contain real records and typically results in less information loss compared to Anonymization.

Advantages

• It can be used for analytics and advanced analytics with minimal impact.
• It ensures that no real individual can be re-identified.
• It is generated with privacy safeguards and can be used without user approval.
• It can be viewed by any user once generalized.
• It is produced by processing all records together.
• It does not require additional security measures.
• It can be generated on demand.
• It can be considered anonymous data within the context of GDPR.
• It can be generated in a manner that avoids being subject to HIPAA regulations.

Disadvantages

• It is slower than Pseudonymization or Anonymization.
• It is not suitable for use cases where re-identification is necessary.
• It requires minimal data to work reliably. The amount of data needed increases with data complexity.