ENISA Data Protection Engineering - From Theory to Practice
ENISA DPE - Anonymisation and Pseudonymisation

ENISA Data Protection Engineering - From Theory to Practice ENISA-DPE-3.1: Anonymisation

Anonymisation removes all means reasonably likely to be used to identify a natural person from a dataset; if successful the data is outside GDPR scope. The report surveys the main anonymisation models including k-anonymity, l-diversity and t-closeness and warns that anonymisation must be assessed against motivated-intruder and re-identification attacks.

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