Pseudonymization Techniques in Python
This presentation is from a talk I gave at Boulder Python in June 2018 (event link).
To see the presentation, visit: frankv.github.io/pseudonymization-in-python_BoulderPython_0618/
Abstract
Protecting user data has always been an important task, but now thanks to GDPR, it's the law! Join Boulder Python's co-organizer Frank for a discussion on data protection using a technique known as pseudonymization. If you're concerned about best practices for protecting user identities in your apps, you don't want to miss this talk!
Outline
- What is pseudonymization?
- Pseudonymization is a data de-identification procedure.
- Why would you do this?
- protect user identities
- secure a dataset from identification
- 🚨 GDPR 🚨
- GDPR from 10,000 feet
-
"I am not a lawyer, I will not answer your legal questions." - @fmdfrank
— BoulderPython (@BoulderPython) June 13, 2018 - What is GDPR?
- The Rules
- What is Personal Data w/ Examples
-
- Who does this effect?
- "The Long Arm of the Law"
- Data Privacy Techniques
- Pseudonymization
- Anonymization
- Pseudonymization Techniques
- Data Masking
- Approximation
- Encryption
- Tokenization 8.Simple Python Example
- Class
propertiesandgetter/setter - A Simple Masking Algorithm
- Django Example
- Pseudonymizing a User model w/
getter/setter - Finishing the Job
- Update QuerySet
- Pseudonym Exclusion
- Update
django-admin
- Pseudonymizing a User model w/
- Demonstration
Notes
You can find the example masking algorithm in examples/simple_masking.py
Talk Nerdy To Me
- 🐦 @fmdfrank
- 📩 frank [at] cuttlesoft [dot] com
- 🐙 Cuttlesoft