Skip to main content

This project implemets basic anonymization operations for event data which are used by process mining techniques.

Project description

Introduction

This project implemets basic anonymization operations for event data which are used by process mining techniques. The anonymization operations are formally explained in the following paper: https://www.researchgate.net/publication/342048551_Privacy-Preserving_Data_Publishing_in_Process_Mining

Ref: implemeted by "Alexander 'DevSchnitzel' Schnitzler" as part of his bachelor thesis at PADS group.

Python Package

The implementation has been published as a standard Python package. Use the following command to install the corresponding Python package:

pip install ppdp-anonops

Usage

Look at the following directory in the Github project to see the samples of usage: "ppdp-anonops/tests"

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ppdp_anonops-0.1.1.tar.gz (15.2 kB view hashes)

Uploaded Source

Built Distribution

ppdp_anonops-0.1.1-py3-none-any.whl (36.1 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page