Context aware, pluggable and customizable data protection and de-identification SDK for text and images

Secure Vault for Customer PII/PHI/PCI/KYC Records

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.

Python Data Anonymization & Masking Library For Data Science Tasks

HideDroid is an Android app that allows the per-app anonymization of collected personal data according to a privacy level chosen by the user.

This repository allows you to anonymize sensitive information in images/videos. The solution is fully compatible with the DL-based training/inference solutions that we already published/will publish for Object Detection and Semantic Segmentation.

Examples scripts that showcase how to use Private AI Text to de-identify, redact, hash, tokenize, mask and synthesize PII in text.

Snaplet Documentation

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

ANJANA is a Python library for anonymizing sensitive data

🎓🔒 Creating, Analyzing and Testing Differential Privacy Protocols, aiming in Data Protection and Anonymization.

Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS

Anonymize sensitive data in your datasets.

Open source PII detection and anonymization tool: easy-to-use, configurable, and extensible

Anonymizer tool for datasets such CSV files

Data anonymization made easy

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

DataAnonymizer is an open-source personal data anonymization tool designed for GDPR compliancy

Data anonymization using Angular 2+

This script generates various types of fake data, such as names, addresses, phone numbers, coordinates, and more, using the Faker library. Users can select the data type and the quantity to generate. The generated data is saved to a JSON file