The European Data Protection Board (EDPB) has released its draft...
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The European Data Protection Board (EDPB) has released its draft Guidelines 01/2025 on Pseudonymisation for public consultation, marking a pivotal step in clarifying one of the GDPR’s most technically misunderstood concepts.
These guidelines define how data can be effectively pseudonymised to mitigate privacy risks while maintaining compliance with the General Data Protection Regulation (GDPR).
In this post, we’ll explore what these new guidelines mean for data controllers and processors, why pseudonymisation remains critical in privacy engineering, and what organizations can do to prepare.
Why Pseudonymisation Matters
Bridging Legal and Technical Gaps
Under Article 4(5) of the GDPR, pseudonymisation refers to processing personal data in a way that it can no longer be attributed to a specific individual without the use of additional information.
While this definition sounds simple, its technical and operational application has long been debated. The new EDPB guidelines aim to clarify this grey area, ensuring consistency between legal interpretation and technical implementation.
Reducing Risk and Strengthening Compliance
Effective pseudonymisation helps reduce risks to data subjects and can support legitimate interest based processing under Article 6(1)(f) GDPR. The EDPB stresses that properly implemented pseudonymisation can enable safe data analytics, AI training, and research while ensuring privacy protection.
Key Takeaways from the EDPB Guidelines
Definition and Scope
The guidelines reaffirm that pseudonymised data remains personal data. Even if identifiers are replaced or removed, data is only truly pseudonymised if the “additional information” that enables re-identification is stored separately and securely.
Pseudonymisation Domain
A major innovation in the draft is the introduction of the “pseudonymisation domain” — the defined environment within which re-identification must be prevented.
This requires organizations to:
- Identify potential adversaries (internal and external)
- Assess whether existing safeguards prevent re-identification
- Ensure that domain specific controls limit who can access linking data
Managing Additional Information
The EDPB highlights that the separation of additional information, such as keys or mapping files, is fundamental. Access controls, encryption, and strict governance must be implemented to keep re-identification risk low.
Cross Border Transfers and Third Parties
When pseudonymised data is shared across borders or with third parties, the pseudonymisation domain may change, requiring reassessment. If external parties could reasonably re-identify the data, additional safeguards (such as contractual controls and encryption) must be added.
How Organizations Should Prepare
1. Perform a Domain & Attribution Risk Assessment
Identify all systems, users, and data flows that interact with pseudonymised data. Define your pseudonymisation domain and assess how easily data could be attributed back to individuals.
2. Evaluate Current Pseudonymisation Techniques
Review existing de-identification methods (e.g., tokenization, hashing, encryption) to ensure they align with the EDPB’s technical and organizational standards.
3. Update Contracts and Data Sharing Policies
Ensure that Data Processing Agreements (DPAs) and vendor contracts explicitly define responsibilities for maintaining pseudonymisation safeguards, especially around re-identification risk.
4. Monitor Consultation Updates
The draft guidelines are still under public consultation. Organizations are encouraged to provide feedback before final adoption and stay updated on revisions to technical expectations.
You can submit feedback using the link below.
Conclusion
The EDPB’s new guidelines make clear that pseudonymisation is more than just removing names from a dataset, it’s a dynamic, context driven process that requires continuous assessment and technical rigor.
For compliance officers, DPOs, and data scientists, this guidance represents a chance to harmonise privacy engineering with regulatory compliance, ensuring data utility without compromising personal privacy.
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