SITA Anonymizer is a tool developed for the anonymization of sensitive data based on the SITA model (Identity, Space, Time, and Activity), enabling fine-grained privacy control over CSV datasets. The app implements the principles defined by Mads Schaarup Andersen, Mikkel Baun Kjærgaard, and Kaj Grønbæk, researchers from Aarhus University (Denmark), who proposed the conceptual SITA model. This model introduces a multidimensional approach to privacy, with five distinct levels per dimension, facilitating the practical application of anonymization strategies. Designed for academic, professional, and industrial use, SITA Anonymizer allows users to apply different anonymization levels to specific dataset columns based on data-type-specific rules. Key features: • Import of CSV files with thousands of records • Classification by privacy dimension (SITA): Identity, Space, Time, and Activity • Mapping of data types such as CPF (Brazilian ID), Phone Number, Name, IP Address, Dates, and more • Application of multiple anonymization rules: generalization, rounding, abbreviation, suppression, and more • Privacy level selection (0 to 4) with per-column visualization • Preview of anonymized data before exporting • Export to CSV format • Automatic k-anonymity evaluation after each transformation • Support for custom data types and rules created and stored by the user With SITA Anonymizer, you gain full control over the anonymization process — from identifying sensitive attributes to securely exporting the anonymized dataset as a CSV file!