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.

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

Named entity recognition framework

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.

가명처리 라이브러리

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

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

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

AWS Blueprint: Automate data masking workflow

Create your own document de-identifier using docdeid, a simple framework independent of language or domain.