Tag: Synthetic Data

Data anonymization transforms sensitive datasets to prevent individual identification while keeping data useful. Within EOSC-SIESTA, two open-source tools help researchers sanitize quasi-identifiers and assess privacy risks by applying advanced anonymity models (like k-anonymity and l-diversity) to protect sensitive tabular data.