Elkoumy / amun
Amun is a framework that achieves privacy-preserving process mining using differential privacy.
☆12Updated 2 years ago
Alternatives and similar repositories for amun
Users that are interested in amun are comparing it to the libraries listed below
Sorting:
- PROVED (PRocess mining OVer uncErtain Data) is a library of functionalities to perform process mining on uncertain event data.☆12Updated 2 years ago
- https://arxiv.org/abs/2009.01561☆23Updated 2 years ago
- Python Implementation of Decay Replay Mining (DREAM)☆27Updated 2 years ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆24Updated 5 years ago
- Learning Accurate Generative Models of Business Processes With LSTM Neural Networks☆30Updated last year
- This is the complementary code repository for the BINet papers.☆27Updated 4 years ago
- A Deep Learning model for business process predictions. Preprint on arXiv: https://arxiv.org/abs/2102.07838☆12Updated 4 years ago
- A toolbox for differentially private data generation☆131Updated last year
- ☆36Updated last year
- ☆39Updated 2 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆64Updated 6 years ago
- Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data☆33Updated 6 years ago
- ☆10Updated last year
- Secure collaborative training and inference for XGBoost.☆105Updated 2 years ago
- This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.☆26Updated 4 years ago
- Privacy-preserving XGBoost Inference☆49Updated 2 years ago
- Differentially Private Conditional Generative Adversarial Network☆31Updated 3 years ago
- An implementation of the tools described in the paper entitled "Graphical-model based estimation and inference for differential privacy"☆102Updated last week
- ☆38Updated 2 years ago
- A Business Processes and Logs Generator☆34Updated last year
- A Simulator for Privacy Preserving Federated Learning☆94Updated 4 years ago
- Code for Canonne-Kamath-Steinke paper https://arxiv.org/abs/2004.00010☆61Updated 4 years ago
- PrivGAN: Protecting GANs from membership inference attacks at low cost☆33Updated 11 months ago
- Automatic process simulation using Simpy and Pm4py.☆18Updated 3 years ago
- Federated Principal Component Analysis Revisited!☆42Updated 3 years ago
- Source code of paper "Differentially Private Generative Adversarial Network"☆69Updated 6 years ago
- SAP Security research sample code and tutorials for generating differentially private synthetic datasets using generative deep learning m…☆23Updated last year
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆134Updated 2 years ago
- ☆43Updated 3 years ago
- Differentially Private Synthetic Data Generation [DP-SDG] - Experimental Setups & Knowledge Base - WORK IN PROGRESS☆12Updated 2 years ago