5
Developing Applications with Differential Privacy Using Open Source Frameworks
In this chapter, we will explore open source frameworks (PyDP, PipelineDP, tmlt-analytics, PySpark, diffprivlib, PyTorch, and Opacus) used to develop machine learning, deep learning, and large-scale applications with the power of differential privacy.
We will cover the following main topics:
- Open source frameworks for implementing differential privacy:
- Introduction to the PyDP framework and its key features
- Examples and demonstrations of PyDP in action
- Developing a sample banking application with PyDP to showcase differential privacy techniques
- Protecting against membership inference attacks:
- Understanding membership inference attacks and their potential risks
- Techniques ...
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