pseudonimizimin

Pseudonymization is a data protection measure that involves replacing identifying information with artificial identifiers, or pseudonyms. This process renders personal data anonymous in such a way that it can no longer be attributed to a specific data subject without the use of additional information, provided that this additional information is kept separately and is subject to technical and organizational measures to ensure that the personal data are not attributed to an identified or identifiable natural person. It is a key concept in data privacy regulations like the General Data Protection Regulation (GDPR).

The primary goal of pseudonymization is to reduce the risk of re-identification. While pseudonymized data is still considered personal data because re-identification is possible with additional information, it significantly enhances security compared to raw, identifiable data. This makes it a valuable technique for data processing, analysis, and sharing, especially when full anonymization is not feasible or desirable.

Common methods of pseudonymization include hashing, tokenization, and encryption. Hashing creates a fixed-size string of characters from data, but it's typically irreversible. Tokenization replaces sensitive data with a non-sensitive token. Encryption scrambles data using an algorithm, requiring a key for decryption. The choice of method depends on the specific data and the desired level of security and usability. Pseudonymization allows for the continued use of data for various purposes while offering a strong layer of protection against unauthorized access and breaches.