SITA Anonymizer

SITA Anonymizer is a powerful tool for anonymizing sensitive data based on the SITA model (Identity, Space, Time, and Activity), enabling fine-grained privacy control over CSV datasets.

The app is built on the conceptual model proposed by Mads Schaarup Andersen, Mikkel Baun Kjærgaard, and Kaj Grønbæk, researchers at Aarhus University (Denmark). The SITA model introduces a multi-dimensional privacy framework with five defined levels for each dimension, allowing customizable and practical anonymization strategies.

Designed for academic, industrial, and research environments, SITA Anonymizer lets you apply customizable anonymization levels to individual columns using rules defined per data type. The app provides a clean and efficient interface to protect personal information while preserving data utility.

Key Features:
• Import large CSV files with thousands of records
• Classify columns by SITA dimensions: Identity, Space, Time, Activity
• Assign data types like CPF, Phone, Name, IP address, Dates, etc.
• Apply multiple anonymization rules: masking, generalization, rounding, abbreviation, suppression, and more
• Define privacy levels (0 to 4) and preview anonymized data per column
• Preview anonymized output before export
• Export anonymized datasets as CSV
• Automatically compute K-anonymity after each transformation
• Support for custom data types and rules, created and saved by the user
• Built with SwiftUI, offering native performance, accessibility, and a clean design

Who is it for?
• Researchers and students working with sensitive data
• Privacy and data governance professionals
• Developers needing anonymized datasets for models or testing
• Teams handling regulated data (LGPD, GDPR, HIPAA)

With SITA Anonymizer, you maintain full control over the anonymization process — from selecting sensitive attributes to exporting compliant CSVs — while adhering to advanced privacy principles like K-anonymity and contextual integrity.