ARX Data Anonymization Tool vs Open Diffix

ARX Data Anonymization Tool is open-source software for anonymizing sensitive personal data and examining privacy risk and data utility. Its graphical application supports data import and cleansing, transformation-rule setup, tailoring anonymized datasets, and analysis of utility and residual re-identification risk. It imports CSV, MS Excel, and relational database data, including MS SQL, DB2, MySQL, and PostgreSQL. Listed methods include k-anonymity, l-diversity, t-closeness, δ-presence, risk-based criteria, and semantic models such as differential privacy. ARX exports displayed tables to CSV and compares input with transformed data using information-loss models, descriptive statistics, and application-specific analyses. Its risk analysis reports prosecutor, journalist, and marketer attack risks, estimates population uniqueness, and can identify HIPAA Safe Harbor identifiers and further quasi-identifiers. A Java library and API can add anonymization capabilities to Java programs. The tool is free under Apache License 2.0 and supports Linux, macOS, Windows, API, and self-hosted options. The maker provides PGP/GPG-signed checksums for download integrity and states the software is provided without warranties or conditions.

Open Diffix is a free, open-source project for anonymizing structured data, available through APIs and self-hosted deployments on Linux, macOS, and Windows. Its SynDiffix Python package generates statistically accurate synthetic data with strong anonymity. It is aimed especially at descriptive analysis, including histograms, heatmaps, column correlations, counts, averages, and standard deviations. You can generate a separate synthetic table for each analytic task and distribute a blob from which others create tables after installing SynDiffix. The project says this approach can preserve anonymity across many column combinations, but blobs currently do not scale well beyond about 10 columns. SynDiffix installs with pip and requires Python 3.10 or later. It can also support machine learning, though the maker says ML use is somewhat less easy. For data containing multiple rows per protected entity, provide the entity identifier separately or anonymity may be compromised. Open Diffix also includes pg_diffix, a PostgreSQL extension for aggregate anonymized answers to a very limited SQL subset; development is paused.