Context aware, pluggable and customizable data protection and de-identification 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.

Mediapipe-based library to redact faces from videos and images

A curated list of resources related to privacy engineering

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

Baseline Recipe for VoicePrivacy Challenge 2022: anonymization systems and evaluation software

A python client used to interact with the Private AI's API

Masking identifiable information from health related documents.

A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxon to identify (and remove) is Homo sapiens. Removal is optional.

Deidentify people's names and gender specific pronouns

Application of our De-identification Framework with open source technologies, enabling enterprises to take ownership of the de-identification process and deploy it in trusted environments.

A data de-identification library written in Go

CliniDeID automatically de-identifies clinical text notes according to the HIPAA Safe Harbor method. It accurately finds identifiers and tags or replaces them with realistic surrogates for better anonymity.

A pre-commit hook to check for PII in your code.

Source code for the paper "Generating Synthetic Training Data for Supervised De-Identification of Electronic Health Records" in Future Internet (2021).

Named entity recognition framework

가명처리 라이브러리

Python package to replace identifiable strings in multiple files and folders at once.

An named-entity-recognition (NER) based anonymizer for archival documents metadata.

AWS Blueprint: Automate data masking workflow