Anonymization methods for network security.

Anonymizing Library for Apache Spark

pyCANON is a Python library and CLI to assess the values of the parameters associated with the most common privacy-preserving techniques.

Anonymization library for python. Protect the privacy of individuals.

ANJANA is a Python library for anonymizing sensitive data

A simple Python package to quickly run privacy metrics for your data. Obtain the K-anonimity, L-diversity and T-closeness to asses how anonymous your transformed data is, and how it's balanced with data usability.

Comparison of the performance of machine learning models applied on anonymized data with different techniques

DataArmor is a cutting-edge tool focused on safeguarding privacy in today's data-driven world using K-anonymity L-diversity and t-closeness privacy model. As the sharing of personal and microdata grows, ensuring the protection of individual identities during data publication and analysis becomes essential.

This repository contains Python scripts to identify attributes in a dataset and subsequently determine the best QID dimension based on privacy gain and non-uniform entropy.

Application of K-Anonymity, L-Diversity, T-Closeness on numerical or categorial Data.

Study of an article in the context of the course "Data anonymization and privacy". About t-closeness, l-diversity and k-anonymity. Implementation of the associated code.