Context aware, pluggable and customizable data protection and anonymization SDK for text and images

ARX is a comprehensive open source data anonymization tool aiming to provide scalability and usability. It supports various anonymization techniques, methods for analyzing data quality and re-identification risks and it supports well-known privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy.

Secure storage for personal records built to comply with GDPR

Library for identification, anonymization and de-anonymization of PII data

Data anonymization using Angular 2+

A free data masking and/or anonymizer library

Implementation of An Efficient Clustering Method for k-Anonymization in Python 2.7

Induction to anonymization of data

Anonymize your Pandas data. Preserve privacy.

ARX is a comprehensive open source data anonymization tool aiming to provide scalability and usability. It supports various anonymization techniques, methods for analyzing data quality and re-identification risks and it supports well-known privacy models, such as k-anonymity, l-diversity, t-closeness and differential privacy.

Data anonymization for ActiveRecord

Neuralyzer is a library and a command line tool to anonymize databases (by updating existing data or populating a table with fake data)

Anonymize your database dumps.

A simple data minimization and anonymization microservice wrapped around go-minimizer

Data anonymization

Sensitive Data Management: Data Discovery and Anonymization toolkit

Data minimization, pseudonymization, and anonymization helpers for Go

Anonymizer: scrambles your confidential production data for use in test environments

MATLAB code for extracting, converting and anonymising files in CTF MEG proprietary format.

A project for generating data defined by a data definition file, the data would be a representation of real data that would be expected. Also enables the anonymisation of Personal identifiable information of data provided in either CSV or SQL connection.

Data Protection and Privacy (90538) final project at UniGe