Sensitive Data Management: Data Discovery and Anonymization toolkit

Distributed Anonymization Platform for SQL databases

📛 An experimental data anonymisation library

A selected collection of my work samples

Data anonymity made simple

Hash data stored in Excel spreadsheet using pandas and Python's hashlib library

DPP - "Anonymizing Transaction Databases for Publication" - AA 2022/23

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

Anonymizing confidential data using the concept of masking.

Exploring US Census microdata, tackling privacy issues, and anonymization. Exercise A delves into quasi-identifiers, anonymization methods, identification risks, and differential privacy. Exercise B involves data loading, k-anonymity, histograms, adding noise for privacy, computing private averages, and analyzing privacy parameter impacts.

Anonymize your database dumps.

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.

Extracting and analyzing user data stored by Facebook using Python and SQLIte

Anonymize data using AES-128 encryption/decryption algorithm.

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

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

Sonarum revolutionizes human-machine communication by securing real-time text, audio, and video streams while remaining fast, secure, and lightweight. It detects and controls sensitive and secure data on-the-fly, ensuring privacy and security without compromising quality.

This repository contains an analysis of the US Census Bureau's microdata from the 2010 census. The current analysis focuses on understanding the privacy threats associated with the non-anonymized dataset and exploring techniques to preserve privacy while analyzing the data.

ANJANA is a Python library for anonymizing sensitive data

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.