pseudonymizáció

Pseudonymizáció is a data processing technique used to replace identifying information in a data set with artificial identifiers or pseudonyms. This process is a key element of data protection and privacy regulations, such as the General Data Protection Regulation (GDPR). The primary goal of pseudonymization is to reduce the risk of direct identification of individuals while still allowing for the data to be analyzed and used for legitimate purposes.

In pseudonymization, direct identifiers like names, addresses, or social security numbers are replaced. For example, a name might be replaced with a unique code or a random string of characters. The original data, which allows for re-identification, is stored separately and securely. This separation is crucial, as it means that without access to the key linking the pseudonyms back to the original identifiers, the data is considered anonymized from the perspective of a user of the pseudonymized dataset.

The benefits of pseudonymization include enhanced data security and privacy, as well as compliance with data protection laws. It allows organizations to leverage valuable data for research, analytics, and product development without exposing individuals to the risks associated with direct identification. However, it's important to note that pseudonymized data is not the same as anonymized data. True anonymization means that re-identification is impossible, even with additional information. Pseudonymization, while a strong privacy measure, retains the possibility of re-identification if the linking key is compromised or accessed.