Anonymization methods for network security.
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Updated
Oct 20, 2019 - Jupyter Notebook
Anonymization methods for network security.
Anonymizing Library for Apache Spark
Repertoire sur l'anonymisation
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.
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.
In an age of widespread data collecting and sharing, the safeguarding of people’s sensitive information has become critical. Facial photos and tabular data frequently contain personal information that, if revealed, can lead to identity theft, discrimination, and other types of harm.
Comparison of the performance of machine learning models applied on anonymized data with different techniques
DB security Semester Homework - MSc Fall 2020
ANJANA is a Python library for anonymizing sensitive data
Prink (Privacy-Preserving Flink) is a data anonymization solution for Apache Flink, that provides k-anonymity and l-diversity for data streams.
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.
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.
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