Data Pseudonymization - Definition
Data pseudonymization is the process of replacing personal data with substitute identifiers or codes that do not allow direct identification of an individual, while enabling continued data processing with a certain level of privacy protection in accordance with GDPR.
Tools Used in Data Pseudonymization
Information systems and algorithms are employed to automatically replace sensitive data with tokens or codes, while maintaining appropriate decryption keys. These tools can operate on local servers or in the cloud, often with AI support.
Benefits of Data Pseudonymization
The process mitigates the risk of personal data disclosure while preserving system functionality and data analysis capabilities. It facilitates GDPR compliance and reduces organizational liability for data processing.
Risks Associated with Data Pseudonymization
Pseudonymized data may still be linked to an individual using additional information, therefore key protection and security measures are required. Improper management of this information creates privacy breach risks.
Examples of Data Pseudonymization Use Cases
In clinical research and analytical systems, patients' personal data are pseudonymized, enabling research to be conducted without revealing the identity of individual subjects.