Supplemental material for: FRUTO: Fuzzy Rules and Test-Driven Optimization - A Methodology for Transparent and Privacy-Preserving Data Anonymization

This is the supplemental material for the paper "FRUTO: Fuzzy Rules and Test-Driven Optimization—A Methodology for Transparent and Privacy-Preserving Data Anonymization" published in XXXXXXX. It contains the original dataset as well as the different anonymizations used as input to evaluate the FRUTO methodology. The supplementary material includes the following files: originaldatasets.zip: contains the original datasets used in our experiment, all provided in comma-separated format (.csv) anonymizeddatasets.zip: contains the field anonymized as well as the antecedent and consequent values for each original dataset provided. In the zip file, each subdirectory contains the data of an anonymization effort (range from 1 to 17). Each file is named with the dataset name (dataset_), anonymized field (anoncolum_field) and the sensitive value (sensiblevalue_field) and the effort (level_effort): e.g. insurance_anoncolum_bmi_sensiblevalue_smoker_level_2.dat To cite this work: C. Augusto, J. Morán, L. Morales, M. Olivero, C. de la Riva, J. Aroba and J. Tuya, “FRUTO: Fuzzy Rules and Test-Driven Optimization - A Methodology for Transparent and Privacy-Preserving Data Anonymization”, Journal Name, XXX, YYY. https://doi.org/XXXXXX