Personal data in the wrong hands can jeopardize the security of individuals. To protect personal data we anonymize or pseudonymize it. Data anonymization is a process of altering identifiable data such as name, gender, age, or other personal information by replacing it with sets of data that make it nearly impossible for every actor to trace the data back to their original owners. Pseudonymization makes this nearly impossible only for unauthorized actors.
A good data anonymizer/pseudonymizer should fulfill certain requirements. Here we collect mainly open-source anonymizers/pseudonymizer. Also, we prioritize tools which require only little programming skill and/or have a GUI or interactive dashboard. Additionally, most researchers we address have to use GDPR compliant tools.
ARX is open-source software for data anonymization. it supports data transformations in a way that ensures user-specific privacy and controls statistical disclosure. This software helps to mitigate attacks regarding privacy breaches. Using ARX we can easily remove direct identifiers such as name or phone number or other personal information. An indirect identifier is used to replace the direct identifier from the data sets. ARX also supports various methods of protecting sensitive data.
Basic Features :
- Open source
- Works both in Windows and macOS
- Supports popular models for protecting data such as syntactic privacy model( K-anonymity, l-diversity, t-closeness, etc.), Statistical privacy model, and semantic privacy model.
- Dedicated GUI which can be used for data visualization
- Able to handle large data sets
- Extracts data from CSV, Excel, and DBMS