Anonymization methods for network security.
-
Updated
Mar 2, 2025 - Jupyter Notebook
#
t-closeness
Here are 16 public repositories matching this topic...
pyCANON is a Python library and CLI to assess the values of the parameters associated with the most common privacy-preserving techniques.
data-science open open-data datascience anonymity data-analysis data-privacy anonymization privacy-preserving k-anonymity l-diversity t-closeness
-
Updated
Aug 25, 2026 - Python
ANJANA is a Python library for anonymizing sensitive data
security data-science data privacy databases open-data anonymity data-analytics data-privacy data-anonymization k-anonymity l-diversity t-closeness
-
Updated
Aug 24, 2026 - Python
Anonymization library for python. Protect the privacy of individuals.
-
Updated
Sep 21, 2024 - Python
Anonymizing Library for Apache Spark
apache-spark apache differential-privacy privacy-preserving k-anonymity l-diversity t-closeness mondrian-anonymization clustering-anonymization
-
Updated
Nov 9, 2023 - Python
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.
-
Updated
Jul 11, 2023 - Python
Agnostic Python library for data anonymazation: anonymizing structured, semi-structured, and unstructured data.
python open-source privacy open-data data-engineering data-privacy gdpr privacy-protection anonymization data-anonymization burkina-faso de-identification data-masking k-anonymity l-diversity t-closeness
-
Updated
Jul 17, 2026 - Python
Comparison of the performance of machine learning models applied on anonymized data with different techniques
data-science machine-learning ml anonymity data-privacy k-anonymity l-diversity t-closeness ml-classifiers
-
Updated
May 17, 2023 - Jupyter Notebook
Scalable, chunk-wise K-anonymization tool based on the Optimal Lattice Anonymization (OLA) algorithm. It is designed to handle large datasets by processing them in manageable chunks, ensuring data privacy while maintaining utility.
encoding chunking ola large-dataset massive-datasets k-anonymity l-diversity t-closeness skald discernibility record-suppression predictive-tagging
-
Updated
Aug 20, 2026 - Rust
DataShield – KMT Anonymity App
-
Updated
Feb 9, 2026 - Jupyter Notebook
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.
-
Updated
Jun 2, 2024 - Python
Data anonymization project using ARX: applying k-anonymity with l-diversity and t-closeness to evaluate privacy-utility trade-offs on a sensitive dataset.
privacy risk-analysis data-privacy data-anonymization k-anonymity l-diversity t-closeness data-utility arx-tool
-
Updated
Sep 1, 2025
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.
privacy mondrian anonymisation data-privacy suppression windows-form-application anonymization masking perturbation privacy-preserving correlation-analysis privacy-preserving-data-mining k-anonymity l-diversity t-closeness correlation-analyses k-anomity privacy-preserving-data-publishing multidimentional-mondrian generlization
-
Updated
Jun 28, 2025 - C#
Application of K-Anonymity, L-Diversity, T-Closeness on numerical or categorial Data.
-
Updated
Jul 6, 2024 - Jupyter Notebook
An open source python library for anonymizating sensitive data.
-
Updated
Aug 9, 2026 - HTML
Improve this page
Add a description, image, and links to the t-closeness topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the t-closeness topic, visit your repo's landing page and select "manage topics."