A curated list of resources related to privacy engineering
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Updated
Sep 28, 2024
A curated list of resources related to privacy engineering
A privacy and security engineering toolkit: Discover, understand, pseudonymize, anonymize, encrypt and securely share sensitive and personal data: Privacy and security as code.
A run anywhere database anonymizer
Private Input Masked Output - PIMO is a tool for data masking (anonymization, pseudonymization, ...).
Overview of tools to de-identify, synthesize and work safely with (sensitive) data
A REST service to pseudonymize and anonymize FHIR® resources.
serverless ☁️ 🚀 , pseudonymizing proxy between Worklytics and your workplace 💼 SaaS data sources' APIs. Data Loss Prevention (DLP) 🛡️🔒 and compliance layer deployable to AWS Lambda or GCP Cloud Functions.
Etalab's Lab IA Pseudonymization Demo source code
Private Prompts Prototype Documentation
A simple pseudonymization service. Your data is not shared with the server.
A very fast and resource-efficient pseudonym service.
Personal data redaction on images based on FHIR patient resources.
AWS Blueprint: Automate data masking workflow
The Personal Data Pseudonymizer is a Python script designed to anonymize sensitive personal information in text. It identifies and pseudonymizes named entities such as people's names, locations, phone numbers, and email addresses by replacing them with asterisks (*).
Redactify is an efficient data redaction tool that secures sensitive text using advanced NLP and rule-based methods. It combines transformer-based NER, regex, and Presidio analysis to detect and mask personal information through full redaction or partial masking—ensuring compliance while preserving data utility.
A simple ReactJS web app for anonymization and pseudonymization of CSV Data
Automated mirror from https://bitbucket.org/medicalinformatics/mainzelliste/
MasKIT: A tool for pseudonymization and anonymization of Czech legal texts.
Node.js implementation of the Crypto-PAn IP address pseudonymisation algorithm
A tool for replacing privacy-sensitive information with synthetically generated alternatives
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