-
PyDP
The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
As the title mentioned, I studied some tutorials about differential privacy and the examples of PyDP, but they only deal with simple cases(structure text). Which paper/direction I should focus on if I want to make the unstructured medical data private? Is it possible to make the data private with some preprocessing before I feed the data into the model? A naive idea is find out the sensitive part(ex : name), change them to non sensitive text manually. Thanks