Additional examples are adjusted to the entries in an automated way - we cannot guarantee that they are correct.
Potential solutions are the combination of pseudonymization with fragmentation and encryption.
However, plain pseudonymization for privacy preservation often reaches its limits when genetic data are involved.
Pseudonymization is an issue in, for example, patient-related data that has to be passed on securely between clinical centers.
The application of pseudonymization to e-health intends to preserve the patient's privacy and data confidentiality.
Privacy functions include AES encryption, data masking, and pseudonymization.
Kameleon, a Pseudonymization product developed by Mastek Ltd.
Pseudonymization is a procedure by which the most identifying fields within a data record are replaced by one or more artificial identifiers, or pseudonyms.
The pseudonym allows tracking back of data to its origins, which distinguishes pseudonymization from anonymization (comment: better distinction is given in ), where all person-related data that could allow backtracking has been purged.
An example of application of Pseudonymization procedure is creation of datasets for De-identification research by replacing identifying words with words from the same category (e.g. replacing a name with a random name from the names dictionary), however, in this case it is in general not possible to track data back to its origins.