qiyuangong / Basic_Mondrian
The raw mondrian is designed for numerical attributes. When comes to categorical attributes, Mondrian needs to transform categorical attributes to numerical ones. This transformations is not good for some applications. In 2006, LeFevre proposed basic Mondrian, which support both categorical and numerical attributes. This repository is an impleme…
☆35Updated 2 years ago
Alternatives and similar repositories for Basic_Mondrian:
Users that are interested in Basic_Mondrian are comparing it to the libraries listed below
- Python Implementation for Mondrian Multidimensional K-Anonymity (Mondrian).☆173Updated last year
- cluster based generalization for k-anonymity☆29Updated 5 years ago
- Implementation of DataFly for K-anonymity, and implemented Laplace Mechanism and Exponential Mechanism for Differential Privacy☆39Updated 6 years ago
- Mondrian for L-diveristy. It's not available now.☆19Updated 5 years ago
- Top_Down_Greedy_Anonymization is a Top-down greedy algorithm data anonymization algorithm for relational dataset, proposed by Jian Xu in …☆10Updated 9 years ago
- Anonymization methods for network security.☆157Updated 2 months ago
- Code for NIPS'2017 paper☆50Updated 4 years ago
- Naive implementation of basic Differential-Privacy framework and algorithms☆48Updated 2 years ago
- QGIS differential privacy processing plugin☆22Updated 9 years ago
- ☆20Updated last year
- 关于2019和2018年的一些东西☆28Updated 5 years ago
- ☆43Updated 3 years ago
- K-Anonymity Simulator☆15Updated 7 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆134Updated 4 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆134Updated 2 years ago
- Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.☆74Updated last year
- Sample LDP implementation in Python☆125Updated last year
- Differential private machine learning☆191Updated 3 years ago
- This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.☆26Updated 4 years ago
- k匿名☆19Updated 3 years ago
- Location Privacy Meter: A tool to model human mobility and quantify location privacy☆16Updated 3 years ago
- Useful tools for differential privacy☆216Updated 2 years ago
- Federated gradient boosted decision tree learning☆68Updated 2 years ago
- Evaluating variety of k-Anonymity techniques.☆54Updated last year
- Analytic calibration for differential privacy with Gaussian perturbations☆47Updated 6 years ago
- A module for the Matrix-Variate Gaussian (MVG) mechanism for differential privacy under matrix-valued query.☆19Updated 4 years ago
- list of differential-privacy related resources☆310Updated 3 months ago
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆33Updated 6 years ago
- A Privacy Preserving Data Mining Platform☆46Updated 12 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆64Updated 6 years ago