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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

  1. What is pseudonymization?
    • Pseudonymization is a data de-identification procedure.
  2. Why would you do this?
    • protect user identities
    • secure a dataset from identification
    • 🚨 GDPR 🚨
  3. 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
  4. Who does this effect?
  5. "The Long Arm of the Law"
  6. Data Privacy Techniques
    • Pseudonymization
    • Anonymization
  7. Pseudonymization Techniques
    • Data Masking
    • Approximation
    • Encryption
    • Tokenization 8.Simple Python Example
    • Class properties and getter/setter
    • A Simple Masking Algorithm
  8. Django Example
    • Pseudonymizing a User model w/ getter/setter
    • Finishing the Job
      • Update QuerySet
      • Pseudonym Exclusion
      • Update django-admin
  9. Demonstration

Notes

You can find the example masking algorithm in examples/simple_masking.py

Talk Nerdy To Me