Pseudonymization

Pseudonymization is a data management technique in which direct identifiers of data subjects are replaced with pseudonyms (or tokens), so that the data can be processed without immediate linkage to a specific individual. The mapping between the pseudonyms and the original identifiers is stored separately and secured with restricted access. This reduces the risk of privacy breaches because the data cannot readily identify individuals without access to the mapping.

Unlike anonymization, pseudonymized data can be re-identified, given access to the re-identification key or additional information. It is often treated as a form of de-identified data under data protection law, notably within the European Union's GDPR, which recognizes pseudonymization as a privacy-preserving technique that can help meet data processing requirements and strengthen security.

Common methods include tokenization (replacing identifiers with tokens), hashing with a salt, encryption with separate key management, and data masking. Effective implementation requires strong key management, separation of re-identification data, and strict access controls. Pseudonymization is particularly useful in analytics, research, healthcare, and customer data processing, where the same data may need to be linked over time without exposing identities.

Limitations include residual re-identification risk, especially when additional data sources are available, and the technique does not render data exempt from privacy laws. Therefore, it should be used as part of a broader data protection strategy that includes minimization, governance, auditing, and regular risk assessment.