pseudonimizeerida

Pseudonimization is a data processing technique where personal data is altered so that it can no longer be attributed to a specific individual without the use of additional information. This additional information, which links the pseudonymized data to the original identifiable data, is kept separately and securely. The goal of pseudonimization is to protect the privacy of individuals by reducing the risk of data breaches and unauthorized access to sensitive information.

This method is often employed in research, analytics, and data sharing scenarios where it is necessary to use personal data for purposes such as statistical analysis or machine learning, but direct identification of individuals is undesirable or prohibited. Pseudonimization is considered a key security measure under data protection regulations like the General Data Protection Regulation (GDPR) in Europe. It is distinct from anonymization, which permanently removes any possibility of re-identification. With pseudonimization, re-identification is still possible, but only by authorized parties who possess the key to link the pseudonyms back to the original data. This allows for a balance between data utility and privacy protection. The effectiveness of pseudonimization depends on the strength of the pseudonymization technique used and the security measures in place to protect the linking information.