Anonymization methods for network security.
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Updated
Oct 20, 2019 - Jupyter Notebook
Anonymization methods for network security.
Repertoire sur l'anonymisation
Anonymization library for python. Protect the privacy of individuals.
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.
ANJANA is a Python library for anonymizing sensitive 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.
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.
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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
DB security Semester Homework - MSc Fall 2020
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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